Claude is launched by Anthropic, covering dialogue, long context reasoning, code agent and enterprise workflow. The official public route is centered around milestones such as Claude 4, Claude Sonnet 4.5, Claude Opus 4.1, Claude 3.7 Sonnet and Claude 3.5 Haiku. The specific available models and prices are subject to the Anthropic real-time page.

Claude

Brief comment in one sentence: Claude is not a simple chat robot, but a multi-layered AI working system with "security alignment + deep reasoning + coding agent" as the differentiated moat - covering the Opus/Sonnet/Haiku three-level model Claude Code coding agent, Computer Use computer operation and MCP protocol ecology. Its core competitive logic is not "the cheapest" or "the most versatile", but "the most reliable choice in scenarios that require fewer errors."

Tool type determination: Claude’s main delivery form is [Productivity/Business Application] (AI assistant product for individuals and enterprises), but the bottom layer also assumes the role of [Basic Large Model/API Infrastructure] (providing model inference services to developers through API), and extends [Agent/MCP/Automation Tools] capabilities (Claude Code, Computer Use, MCP Connectors). This article is developed according to the structure of main form as the main form and sub-form as the supplement, and the in-depth content of the basic large model is integrated into the technical advantages and API-related chapters.

Claude’s core parameters and statistics

Claude is Anthropic's product portal for end users. Behind it is a product matrix composed of the three model lines of Opus / Sonnet / Haiku, Claude Code coding agent, Computer Use computer operation capabilities, and a complete set of enterprise collaboration tools. It is not a single chatbot, but an AI working system delivered with a four-layer structure of "conversational interface + API platform + Agent framework + enterprise integration".

Dimensions	Current public specifications
Product form	Web / iOS / Android / Desktop client Claude Code (IDE/terminal), Claude Platform API
Model lines	Opus (flagship), Sonnet (main force), Haiku (lightweight), each line covers different capabilities-cost gradient
Context window	The current model listed on the official model page supports long context. The specific token upper limit is subject to the Anthropic document
Reasoning mode	Hybrid reasoning, the same model supports switching between "immediate answer" and "extended thinking"
Cloud platform access	AWS Bedrock, Google Cloud Vertex AI, Microsoft Foundry
Enterprise capabilities	SSO/SCIM, Audit Logs, Compliance API, HIPAA-ready, organization-level Skills/Connectors management and control

Hierarchical logic of the three-level model: Opus is geared towards the highest complexity tasks - mathematical proofs, cross-file code reconstruction, multi-step agent planning. It has the highest unit token cost but also the highest output quality limit. Sonnet is a daily production workhorse, providing a balance of power and cost in coding, tool invocation, and most knowledge work scenarios. Haiku focuses on low-latency and high-throughput scenarios - simple classification, summary, and chat completion. It is the default option for cost control in large-scale deployment. The pricing difference between the three lines makes it possible to use a mixed calling strategy of "Sonnet's main force + Opus' attack + Haiku's scale".

The practical significance of hybrid reasoning: Claude is one of the few API products that allows users to switch between "straight out" and "deep thinking" within the same model. This means developers don’t need to prepare dedicated inference model endpoints for tasks that require deliberation - the same API call can control the inference budget through the thinking parameter. This is particularly valuable for applications where most queries are simple and occasionally require complex reasoning (such as customer service systems - 90% general Q&A + 10% escalation): you don't have to pay the high cost of the whole process for 10% of complex queries.

Breadth of coverage of product form: Claude's product line has gone beyond traditional chat assistants - Claude Code is an in-terminal Agent for developers, Claude Cowork is an enterprise collaboration space for non-technical teams, and Claude Security and Project Glasswing are for security operation scenarios. This multi-product layout means that judging Claude's "actual capabilities" cannot only rely on claude.ai's chat experience, but needs to look at the independent capability boundaries of specific product forms.

Claude’s users and market recognition

Claude's market position is built on two parallel tracks: the C-side acquires massive individual users through the claude.ai free tier, and the B-side penetrates regulated industries through enterprise subscriptions and cloud platform cooperation.

C-side individual user market: Claude's free tier strategy is relatively restrained - the Free package provides capabilities such as network search, memory, file processing, remote MCP Connectors and extended thinking, which is a relatively comprehensive feature coverage among the free tiers of mainstream AI assistants. However, claude.ai is not directly available in a large number of regions (including mainland China), which limits the ceiling of its C-side scale. In available areas, Claude relied on Anthropic's "security AI" narrative to acquire a number of high-value users - education, research, and legal practitioners who are sensitive to content security. Different from ChatGPT’s universal coverage, Claude’s user profile is more biased toward “professional users who require in-depth reasoning and credible output.”

Developer and Engineering Community: Claude’s influence among the developer community is mainly established through benchmark results on Claude Code and SWE-bench. After Claude Code enters the terminal and IDE, Claude changes from a "dialog window" to a "project collaboration tool". Developer tools such as Cursor, Replit, and Bolt have built-in Claude models, further positioning the Sonnet/Opus series as one of the preferred models for code generation. According to Anthropic’s official customer quotation page, GitHub, Rakuten, Notion, Databricks, Atlassian, Zapier, Vercel and other companies have disclosed feedback on using Claude - these cases cover multiple tracks such as developer tools, enterprise productivity, and financial technology.

Enterprise-level adoption and regulated industries: Anthropic showcases customized solutions for industries such as financial services, legal, life sciences, healthcare, education, and government on its official website as independent solution pages. This is different from generic API calls - it means Anthropic has made product-level adaptations for the data compliance, output review and auditing requirements of these industries. The SCIM Directory Synchronization Audit Logs, Compliance API and HIPAA-ready certification provided by the Enterprise Edition are prerequisites for entering regulated industries such as finance and healthcare. Anthropic’s cooperation with large organizations such as KPMG, PwC, and Gates Foundation shows that Claude is penetrating into high-value knowledge work scenarios.

Channel advantages of multi-cloud ecosystem: Claude has settled on three cloud platforms: AWS Bedrock, Google Cloud Vertex AI and Microsoft Foundry at the same time, which is rare among large model manufacturers. For enterprise buyers, this means that Claude can be called directly within the existing cloud procurement framework - no additional supplier onboarding process is required, and the compliance and audit path is clearer. Specifically on AWS, Claude has launched a US-only inference option, providing a compliance path for US public sector customers with data residency requirements.

Position in the market competition landscape: Claude's differentiated competitive point lies in the trinity of "security + reasoning + agent" - compared with the multi-modal and large-scale coverage of GPT-5.5, Claude emphasizes output reliability and controllable reasoning; compared with Gemini's native search capabilities and ultra-long context, Claude emphasizes the stability of Agent execution and tool invocation. This positioning gives it a competitive advantage in scenarios that require "less errors" such as coding, legal document analysis, and long-term agents, but it falls behind competing products in scenarios such as creative writing, long-tail knowledge Q&A, and multi-modal generation.

Claude’s cost advantage

Claude's cost structure must be viewed separately from three tiers: consumer-level subscription API calls and enterprise deployment. Its price strategy is not "the lowest price in the market", but "providing clear tiered options for different capabilities and cost requirements."

C-side/Personal Subscription Cost: The Free package covers basic conversation, search and file processing capabilities at zero cost, which is sufficient for light users. The Pro plan at $17/month annually ($200/year upfront) is mid-range pricing for current mainstream AI assistants—between ChatGPT Plus ($20/month) and Gemini Advanced (~$23/month). Max starts at $100/month and offers 5x or 20x Pro usage for high-frequency users. The hidden cost is that the usage limit of the Pro package does not disclose the specific token or maximum number of conversations, and users may experience speed degradation during peak periods. When used frequently, the actual unit cost (USD/million tokens) of the Max package may be lower than that of Pro, but users need to estimate their own usage to verify it.

API Call Cost: Anthropic’s API pricing is arranged in a model line gradient – ​​Haiku < Sonnet < Opus. The following is a rough range comparison of API pricing for each major model (subject to Anthropic’s official real-time page):

Model line	Input price (per million tokens)	Output price (per million tokens)	Cache hit input price	Cost-effectiveness positioning
Opus series	Highest grade	Highest grade	About 10% of input price	Highly difficult reasoning and coding
Sonnet series	Mid-range	Mid-range	About 10% of input price	Daily production main force
Haiku series	Lowest grade	Lowest grade	About 10% input price	High throughput, low latency scenario

Prompt Caching and Batch Processing are two key levers to reduce API costs: the input price can be reduced by about 90% when the cache hits, which is suitable for scenarios where the system prompt words and dialogue prefixes are fixed; batch processing discounts are suitable for non-real-time batch analysis tasks. For long-context RAG applications, whether the cache is properly utilized may be the difference between monthly API fees ranging from 1,000 yuan to 10,000 yuan.

Enterprise deployment cost: When calling through the cloud platform (Bedrock/Vertex AI/Foundry), the price markup and the cost of the cloud platform itself need to be included in the total cost. The enterprise version is priced through negotiation based on seats and compliance requirements and is not disclosed to the public. Private Assessment: Anthropic does not publicly provide self-hosted model weights (it is not open source), so the only path for enterprise private deployments is to run in a compliance zone via the cloud platform. This means that enterprises cannot reduce inference costs by building their own GPU clusters, and the total cost is completely controlled by the pricing strategies of Anthropic and the cloud platform. For large-scale enterprises with large inference needs, you need to apply for dedicated throughput capacity and discounts from the business team, rather than directly controlling marginal costs through self-hosting like the open source model.

Enterprise Decision Mapping of Three-Tier Cost Structure: For small teams and development projects, starting with a Pro subscription or API pay-as-you-go is a reasonable choice - you can experience full functionality without signing a long-term contract. For medium and large enterprises, it is recommended to conduct 1-3 months of POC verification through the cloud platform (Bedrock/Vertex AI) to obtain the actual token consumption distribution and cost benchmark, and then apply for a dedicated capacity discount from the Anthropic business team. For regulated industries, compliance-related auditing, data residency, and HIPAA provisions should be factored into the assessment as part of the cost—compliance capabilities are typically provided at the Team/Enterprise level.

Competitive product pricing comparison table

Comparative dimensions	Claude (Anthropic)	ChatGPT (OpenAI)	Gemini (Google)	DeepSeek
Individual subscription starting price	Free / Pro $20/month	Free / Plus $20/month	Free / Advanced ~$23/month	Free / Pay-as-you-go
API flagship model price range	Highest (Opus)	Highest (GPT-5.5)	Medium to high (Gemini 3 Pro)	Extremely low (V4 Flash)
API main model price range	Medium (Sonnet)	Medium (GPT-5)	Medium (Gemini 3 Flash)	Extremely low
Open source model weights	❌ Not open source	❌ Not open source	❌ Not open source	✅ Partially open source
Free tier functional completeness	Medium (full functionality but usage restrictions)	Medium	High (Google ecosystem integration)	Medium
Enterprise Compliance Certification	HIPAA-ready, SOC2	HIPAA, SOC2	HIPAA, SOC2	Undisclosed
Inference mode flexibility	Hybrid inference (same model switching)	Independent inference model endpoint	Gemini 3 Deep Think	Independent inference model

Claude’s main features

Claude's functional system is not a simple extension of dialogue capabilities, but a modular capability set built around the four main lines of "text understanding - code execution - agent action - enterprise integration".

• Conversation and long article content generation: covering daily Q&A, long article writing, translation, rewriting and research review. Web/mobile/desktop three terminals are fully covered, and the free tier supports online search, memory and file upload. Synergy effect: The results of online searches can be directly injected into long-form writing, and the memory ability makes continuous writing across sessions possible—for example, a research project can accumulate background information, first drafts, and revised versions in multiple rounds of conversations. Claude's memory mechanism can recall previous conclusions and avoid repeated input of context.

• Code Understanding and Software Engineering: Claude Code sinks the coding agent to the IDE and terminal, supporting cross-file editing, debugging, refactoring, test generation and CI workflow integration. Opus/Sonnet maintains cutting-edge performance on benchmarks such as SWE-bench. Expert view: The unique value of Claude Code lies in "asynchronous background execution" - developers can start long-term coding tasks (such as large-scale refactoring, dependency upgrades, test completion) and continue working after Claude Code starts, and receive the results in the terminal after the task is completed. This mode avoids the linear waiting of "one question and one answer" in traditional conversational coding, making the coding agent more like a collaborator rather than a conversational tool.

• Agent and Workflow Orchestration: A complete Agent capability stack is formed through the three major mechanisms of Tools (function call), Computer Use (computer operation), and Connectors (remote MCP). Tools are responsible for interacting with the API, Computer Use is responsible for interacting with the GUI, and Connectors are responsible for synchronizing with the enterprise data system. Hidden linkage: The combination of the three can form a link - the Agent queries the order API through Tools, operates the backend system in the browser to complete the return process through Computer Use, and then writes the results back to the CRM through Connectors. This cross-capability orchestration allows Claude to execute end-to-end business processes rather than point tasks.

• Computer Use: Claude is one of the first manufacturers to deliver "model direct operation of computer interface" as a product capability. Computer Use completes browser and desktop automation through screenshot analysis + coordinate positioning + action execution. Actual Availability: Computer Use performs well on structured web page operations (purchasing process, data entry, customer onboarding), but its stability still fluctuates on complex front-end rendered pages (dynamic component Canvas applications). It is recommended for browser operations with high frequency repetition and low fault tolerance cost. It is not suitable for design tool operations that require pixel-level accuracy.

• Enterprise Collaboration and Data Connectivity: Claude for Slack / Microsoft 365 / Outlook / Chrome embed models into existing collaboration contexts within the enterprise. Projects provides team-level knowledge space, Skills supports custom behavior configuration, and Remote MCP Connectors are open in the Free layer. Actual benefits: For teams that already heavily use Slack or Microsoft 365, Claude's integration can reduce the context switching cost of "open claude.ai → paste context → switch back to the office application". Especially in MS Teams and Outlook, Claude can be directly called for email summaries and document Q&A, which immediately improves daily office efficiency.

• Security and Compliance Features: The Enterprise Edition provides SSO/SCIM directory synchronization, Audit Logs, Compliance API compliance interface and HIPAA-ready certification. Organization-wide control of Skills and Connectors allows IT administrators to centrally set which external tools can be used by employees. Threshold Tip: Compliance functions are concentrated in the Team/Enterprise layer, and are not available in Pro and below packages. Before purchasing, enterprises need to confirm whether the required compliance certifications (such as SOC2, HIPAA coverage for specific businesses) are provided in the selected package.

Claude’s model and version evolution

Claude's version evolution is based on three model lines (Opus / Sonnet / Haiku) as the skeleton. Each line is independently iteratively updated, forming a version rhythm of "flagship exploration → main undertaking → light coverage".

Opus Line: Upgrade node for flagship capabilities

The Opus line is Claude's ability ceiling, carrying the most complex reasoning and coding tasks.

• Claude Opus 4.1 (2025-08-05): A direct upgrade of Opus 4, focusing on improving the accuracy of multi-step reasoning in real encoding and Agent tasks. Compared with the previous generation, Opus 4.1 achieves measurable improvements in cross-file code editing and task completion rates for long-lasting Agents. Positioning significance: Opus 4.1 establishes Claude's competitive advantage in the direction of "high-difficulty coding agents" - it is not the fastest or cheapest model, but it is likely to be one of the models with the highest output accuracy on code agent benchmarks such as SWE-bench.

• Claude Opus 4 (2025-05-22): The first flagship of the Claude 4 series, which allows Claude Code to perform long-term coding tasks in the background for the first time. This version introduces the "asynchronous Agent execution" mode, extending Claude's usage paradigm from "conversational" to "collaborator".

Sonnet Line: Performance baseline for workhorse models

Sonnet lines carry most production workloads, finding a balance between power, speed, and cost.

• Claude Sonnet 4.5 (2025-09-29): An important version of Sonnet for Agent, coding and computer use. Compared with the previous generation, Sonnet 4.5 has been specifically optimized for the consistency of tool calls, the stability of complex multi-step tasks, and the reliability of computer use. User Perception Difference: The core improvement of Sonnet 4.5 is not in "knowing more", but in "executing more stably" - this is of substantial significance to Agents and automation tools, but users in conversation scenarios may not feel it clearly.

• Claude Sonnet 4 (2025-05-22): Released on the same day as Opus 4, it is an overall improvement based on Sonnet 3.7, especially in terms of encoding and structured output. Positioned as a cost-effective production workload model.

• Claude Sonnet 3.7 (2025-02-24): Claude's first hybrid inference model, and Claude Code was released at the same time. This was the starting point for the expansion of Claude's product line from single chat to coding agents. Hybrid reasoning mode allows the same model to switch between quick answers and deep thinking, a design that has been retained and enhanced in subsequent versions.

Haiku Line: The speed benchmark for lightweight models

The Haiku line focuses on low-latency and high-throughput scenarios and is the lowest unit cost option among Claude APIs.

• Claude Haiku 3.5 (2024-10-22): A generational jump in the Haiku series, surpassing the previous generation Opus 3 in multiple benchmarks while maintaining Haiku's consistent speed and cost advantages. Engineering Value: Haiku 3.5 demonstrates advances in model compression and distillation technology, enabling lightweight models to reach levels close to flagship models on simple inference tasks, which is of great significance for cost-sensitive scenarios that require large-scale deployment.

Timeline of key milestones in version evolution

Version	Release Date	Category	Core Changes
Claude Haiku 3.5	2024-10-22	Haiku	Lightweight jump, surpassing Opus 3 on multiple benchmarks
Claude Sonnet 3.7	2025-02-24	Sonnet	The first hybrid inference model + Claude Code released
Claude Opus 4 / Sonnet 4	2025-05-22	Opus/Sonnet	Claude 4 series flagship, asynchronous Agent execution
Claude Opus 4.1	2025-08-05	Opus	Multi-step reasoning and coding accuracy improvement
Claude Sonnet 4.5	2025-09-29	Sonnet	Agent coding and computer usage stability optimization

Engineering interpretation of version pedigree

Claude's version naming and iteration rhythm have their own internal logic: Opus is always released first to establish a capability baseline, Sonnet then takes over and optimizes usability, and Haiku is finally compressed into an efficient version. The three lines can be upgraded independently, which means that enterprise users can keep Sonnet as the main production model and only switch to Opus to handle difficult tasks when needed, without having to wait for all models to be upgraded to the same version. This configuration strategy provides greater flexibility between cost control and stability.

Claude’s technical advantages

Claude's technical advantage is not only the advancement of model capabilities, but also reflected in the depth of engineering in the three dimensions of inference control, security governance, and ecological protocols. As the role of simultaneously carrying [basic large model/API infrastructure], the following is expanded from the four technical dimensions of performance throughput, adaptation boundary, architectural link and security governance.

Performance and Throughput

Technical indicators	Claude's current performance (subject to official data and documents)
TTFT (first word delay)	Straight-out mode: low latency; Extended thinking mode: first word delay increases significantly (due to internal CoT generation), the specific value is subject to actual measurement
Output rate	There is a big difference in different model lines and inference modes. Haiku is the fastest and Opus is the slowest in extended thinking mode
TPM/RPM frequency control	The rate limit listed in the Anthropic API document shall prevail, Free/Pro/Max/Enterprise levels are different
Concurrency and long-term stability	The enterprise version supports dedicated throughput capacity, and standard APIs are shared by tier quotas
Long context scenario	1M token context window, but the complexity of attention calculation under long context leads to increased latency

Differences in TTFT's reasoning mode: In the straight-out mode, Claude's first-word delay is comparable to similar models; however, after extended thinking is enabled, the model will first generate a long chain-of-thought before responding, and the first-word delay may increase from hundreds of milliseconds to several seconds. This is crucial for real-time interaction scenarios (such as customer service chat, real-time translation) - developers need to make a trade-off between response quality and first word delay, and make fine-grained adjustments through the budget_tokens of the thinking parameter.

Adaptation Boundary: Claude's best scenarios are coding, structured reasoning agent tasks, and long document analysis - these tasks require multi-step logical chains and low illusion output. The scenarios that Claude is least good at include: creative writing (the output is conservative, and the style diversity is lower than the GPT series), ultra-long contextual role-playing (limited by security alignment, and the proportion of rejection responses is high), and multi-modal generation (Claude focuses on understanding, and image/video generation is not within the main scope). In the "code + agent" scenario, the overall accuracy and tool call consistency of the Sonnet series are higher than most competing products at the same price point.

Implementation mechanism of Hybrid Reasoning

Claude implements both Non-think and Extended Thinking modes within the same model. Mechanically, extended thinking allocates additional computing budget to chain-of-thought (CoT) generation during reasoning, allowing the model to build a longer internal reasoning chain before answering. Effect Difference: In tasks such as mathematical proof, boundary condition analysis, and multi-step planning, the extended thinking mode can significantly improve the correctness of the final answer; while in tasks such as translation, summarization, and information retrieval, the straight-out mode reduces latency by 30-50% while ensuring quality. Control granularity: Developers can adjust the inference budget through API parameters to make a fine-grained trade-off between "guaranteing answer quality" and "controlling delay costs" - this is not an either-or switch, but a continuous control surface.

Technical costs and benefits of 1M token long context

Claude's long context capabilities build on Transformer's context expansion technology, enabling it to process an entire technical manual or multiple long documents in one go. Actual benefits: In long document analysis scenarios, 1M context means that there is no need to chunk the input (chunking), avoiding the classic problem of "cross-chunk information loss". Technical cost: The longer the context, the quadratic complexity of attention calculation will lead to a significant increase in latency. The first word delay of a long context under high token count may reach several seconds, which is not suitable for real-time interaction scenarios. The most applicable scenario for Claude's long context is to enter a long document at once and then do multiple rounds of questions and answers (such as reviewing a 300-page contract), rather than continuous long conversations.

Architectural design of Agent and tool invocation

Claude's Agent capabilities are implemented through the three-layer architecture of Tools (Function Calling), Computer Use and MCP Connectors. The Tools layer provides a standard function calling interface, allowing the model to call external APIs; the Computer Use layer controls desktop applications through screenshot analysis and coordinate positioning; the MCP (Model Context Protocol) layer provides a unified tool discovery and data connection standard. Architecture link: User Prompt → Claude inference → call Tools/Computer Use/MCP → execution results returned to Claude → generate final output. The standardization significance of MCP is that developers only need to write MCP Server once and can reuse the same set of tools in any AI client that supports MCP, without having to implement different tool calling protocols for each model.

Technical investment in security governance system

Anthropic’s engineering investment in security exceeds that of most similar manufacturers. Responsible Scaling Policy (RSP) defines security thresholds and monitoring mechanisms for model capabilities; System Card provides transparent capability boundaries and known limitations for each critical version; Claude's Constitution provides an auditable value alignment framework for model behavior. Engineering Implications: For companies purchasing Claude, Anthropic’s security documentation system can serve as a reference material for model audits and compliance acceptance—especially in financial and medical regulatory scenarios, where the availability of System Cards and RSPs may be an amount of transparency that other model vendors have not yet provided.

Engineering adaptation for multi-cloud deployment

Claude's deployment on AWS Bedrock, Vertex AI and Microsoft Foundry is not a simple API proxy, but inference optimization and compliance adaptation for each cloud platform. For example, Claude on AWS supports US-only inference options to ensure that inference is completed within the United States and meets the data residency requirements of the public sector; Claude on Vertex AI integrates Google's IAM and data governance system. This means enterprises have the flexibility to choose deployment channels based on data sovereignty, compliance requirements and existing cloud procurement contracts.

How to use Claude

Claude's access paths range from zero-threshold free chat to enterprise-level API integration. There are significant differences in the capability range and billing methods of different paths.

Usage Quick List

Access method	Entrance	Suitable scenarios	Fees
Web/App	claude.ai, iOS/Android/Desktop	Daily conversation, writing, research, lightweight coding	Free/Pro/Max subscription
Claude Code	Terminal/IDE, Pro+ package enabled	Coding Agent, automation, batch code refactoring	Pro/Max/Team/Enterprise
Claude Platform API	platform.claude.com	Self-built product Agent service, system integration	Pay-as-you-go (requires binding payment)
AWS Bedrock	AWS Console	Enterprises with AWS presence, compliance scenarios	AWS channel pricing
Vertex AI	Google Cloud Console	Enterprises with existing GCP environment	GCP channel pricing
Microsoft Foundry	Azure AI Foundry	Enterprises with an Azure presence	Azure channel pricing

The best path for individual users: Start with the Free package of claude.ai and verify the quality of Claude in your own usage scenarios. If you find you need Pro features like Claude Code, more models, or Microsoft 365 integration, then upgrade to the Pro plan ($17/month per year for better value). The core capability difference between Free and Pro is not in the quality of the models (both can use the Sonnet series), but in the availability of coding tools and enterprise integrations.

Quick Integration for Developers: Calling through the Claude Platform API is the most flexible way. The following is an example of calling the Python SDK (please refer to the official documentation for parameters):

import anthropopic

client = anthropic.Anthropic(
    api_key="<YOUR_API_KEY>" # Obtained from platform.claude.com
)

message = client.messages.create(
    model="claude-sonnet-4-5", # Subject to the official currently available model ID
    max_tokens=4096,
    thinking={"type": "enabled", "budget_tokens": 2048}, # Enable extended thinking
    messages=[
        {"role": "user", "content": "Analyze the potential risk points in the following contracts and provide modification suggestions."}
    ]
)

print(message.content[0].text)

Key parameter description: The thinking parameter is used to control hybrid inference - set the inference budget through budget_tokens, and the model will decide whether in-depth thinking is required within the limit. max_tokens controls the total length of output (including inference tokens). The model parameter needs to use the currently available ID listed in the Anthropic model document, and the model name will change due to version updates. temperature default value is 1.0, it is recommended to use 0.0-0.3 for coding tasks to reduce randomness, and 0.7-1.0 for creative writing to increase diversity. stream=True enables streaming output, reducing TTFT awareness for real-time applications.

Claude Code’s core operating mode: Run the claude command in the terminal to start the interactive coding agent. Developers can describe coding tasks in natural language (such as "refactor the payment module to extract the hard-coded rates to the configuration file"), and Claude Code will autonomously perform cross-file editing, testing, and verification. Operation Close: Describe task → Claude Code analyzes the code base → execute changes → run tests → output diff for review. Claude Code Enterprise additionally provides organization-level code repository access, approval processes, and audit logs.

Agent/automation tool deepening: Tool open list and architecture link

Based on Claude's positioning as an Agent platform, the following is a list of its core Tool behaviors exposed to the model:

• tools / tool_use: Standard Function Calling interface, allowing models to call external APIs defined by JSON Schema
• computer: Computer Use tool, supports screenshot (screenshot), mouse_move, click, type, key, scroll and other operations
• mcp_connectors: standardized tool discovery and invocation of remote MCP protocol, supports any MCP Server registration
• text_editor: Claude Code’s built-in file editing tool, supports write, edit, view, diff operations
• bash: Claude Code’s built-in terminal command execution tool, supports command execution and output acquisition

Architecture Link (text graphic):

User Prompt
    ↓
Claude inference engine (Sonnet/Opus)
    ↓ ├── Straight out mode → generate response directly
    ↓ └── Extended Thinking → Internal CoT → Generate Response
    ↓
Tool decision-making layer
    ├── tools (Function Calling) → External API
    ├── computer (Computer Use) → Browser/GUI operation → Screenshot upload → Continue operation
    ├── mcp_connectors → MCP Server → Enterprise Data System
    ├── text_editor → file editing → diff output
    └── bash → Terminal command execution
    ↓
Execution result return → Claude inference → final output

Engineering Pitfall Guide (Agent/Automation Scenario)

1. Dead-end loop and Token explosion control: Claude Agent may fall into repeated operation loops in complex multi-step tasks (such as continuously trying the same failed API call), resulting in an explosion of Token consumption. Solution: Use max_steps or timeout parameters to limit the maximum number of tool calls; make it clear in the system prompt that "the same operation will terminate if it fails twice"; use Anthropic's Usage API to monitor token consumption in real time.
2. DOM/Exception context overload: Computer Use When processing complex web pages, screenshot parsing may cause the context to be filled with a large number of DOM descriptions. Solution: Use visible area extraction (only return the visible part of the viewport instead of the full page); replace full DOM rendering with accessibility tree; poll for screenshots of page regions with more than 50 elements.
3. Security and Ultra-privilege Governance: Claude Agent may perform irreversible operations (such as deleting database records, publishing content, and transferring money) when it has Tools permissions. Solution: Set a manual confirmation point (Human-in-the-loop) for irreversible operations; use read-only mode (read-only) as the default in the Tools definition; implement a whitelist mechanism for MCP Connectors to limit the scope of tools that the model can call.

Cost reduction techniques in API calls

• For production scenarios where the system prompt word is fixed, use Prompt Caching to reduce the input token cost (a cache hit can reduce the input price by about 90%)
• For non-real-time batch analysis, use the Batch Processing API to get discounts
• Use Sonnet as your workhorse model for the vast majority of tasks, switching to Opus only when you need the highest quality output
• Use Haiku models specifically for simple tasks (e.g. classification, summarization, content moderation) instead of using flagship models to handle light loads

Claude’s Product Pricing

Claude's pricing system progresses through four layers: "Personal Subscription → Team Collaboration → API Call → Enterprise Agreement". Each layer has different capability boundaries and billing logic.

Individual and Team Subscription Tiers:

Package	Monthly fee	Core content	Suitable for the crowd
Free	$0	Basic Claude Conversation, Network Search, Memory, File Processing, Remote MCP Connectors, Extended Thinking	Light Personal User
Pro	$20/month ($17/month annually)	Free + Claude Code, Cowork, Projects, Research, more models M365 integration	Individual professional users
Max (5x)	$100/month	Pro 5 times usage, high output limit, early access to new features, priority access during peak periods	High-frequency individual users
Max (20x)	$200/mo	Pro 20x usage	Extremely high users
Team	Pricing by Seat	Max + SSO, Domain Takeover, Usage Analysis, Organizational Level Management	Team
Enterprise	Business Negotiation	Team + SCIM, Audit Logs, Compliance API, HIPAA-ready, custom data retention	Medium and large enterprises

API call layer: Pricing by model line and functional features. Core dimensions include input tokens, output tokens, Prompt Caching (cache hits vs misses), Batch Processing (batch discounts), and region reasoning (for example, US-only regions may have different prices than standard regions). The specific value is subject to the real-time page of https://claude.com/pricing. Billing dimension tip: API calls don’t just look at the unit price of the model - the usage of Prompt Caching, whether Batch Processing is enabled, and whether additional features such as Computer Use are used will significantly affect the final monthly fee. It is recommended to use the cost tracking tool provided by Anthropic to monitor token consumption distribution in actual projects.

API call example (including key parameters)

The following is an example of a standard API call to Curl (for endpoints and model IDs, please refer to the official documentation):

curl https://api.anthropic.com/v1/messages \
  --header "x-api-key: <YOUR_API_KEY>" \
  --header "anthropic-version: 2023-06-01" \
  --header "content-type: application/json" \
  --data '{
    "model": "claude-sonnet-4-5",
    "max_tokens": 4096,
    "temperature": 0.7,
    "stream": true,
    "thinking": {
      "type": "enabled",
      "budget_tokens": 2048
    },
    "messages": [
      {"role": "user", "content": "Use Python to implement an LRU cache, supporting expiration time."}
    ]
  }'

Enterprise Agreement Layer: Negotiated by the Anthropic business team, usually involving the following terms - dedicated throughput capacity (Guaranteed Throughput), model version switching window (advance notice period), data residence area selection, compliance certification coverage (SOC2, HIPAA, etc.), SLA guarantees, and audit cooperation obligations. Specific prices and terms are subject to the enterprise contract.

Cost-performance positioning compared with competing products: Claude is not positioned as the "cheapest AI assistant" - its Free tier does not provide unlimited calls, and the price of the Pro tier ($20/month) is the same as ChatGPT Plus but higher than Gemini Advanced (about $23/month but includes Google ecosystem integration). Its cost-effectiveness advantage is reflected in the "capability-cost ratio" of the Sonnet series - for encoding and agent scenarios, Sonnet's output quality and tool call stability are better than most competing products in the same price range. But for pure dialogue and content generation scenarios, users will find that competing products provide more free credits or richer ecological integration at the same price.

Application scenarios of Claude

Claude's application scenario distribution is highly related to its technical advantages - it performs most prominently in scenarios that require deep reasoning, code agents, long context analysis and output reliability.

• Software Engineering and Code Agent: This is Claude's most competitive scenario. Claude Code performs cross-file refactoring, dependency upgrades, test generation, and code reviews in the terminal. Cost reduction and efficiency improvement: Cross-file reconstruction of a medium-to-large project (100,000+ lines of code) requires 2-3 engineers 1-2 weeks to complete using traditional manual methods; through Claude Code, engineers can complete the core change plan design within 1-2 hours, and the remaining time is used to review and debug the diff generated by Claude. After comprehensive deduction, the working hours of this scenario can be compressed from about 80 people·days to about 15-20 people·days (including review time), a reduction of about 75%, but there are points in the review that cannot be skipped. Boundary Tip: Claude Code has reduced reliability when dealing with highly coupled old code (spaghetti code without test coverage) in legacy systems. It is recommended to do a full code review of the critical path generation results.

• Agent and Business Process Automation: Through the combination of Computer Use, Tools and MCP Connectors, Claude can perform long-term automation tasks across systems - such as "Export new customers from CRM every day → Log in to the backend system in the browser to create an account → Send welcome emails → Notify sales follow-up in Slack". Cost reduction and efficiency improvement: For repetitive business processes that need to span multiple SaaS tools, Claude Agent can compress the execution time from manual 15-30 minutes to 2-5 minutes/time, and reduce human errors in cross-system switching. Based on 50 operations per day, approximately 10-20 people-hours of operating manpower can be released per day. Implementation limitations: Computer Use still has a failure rate in complex front-end interactions (drag and drop Canvas graphic operations, verification codes), and is not suitable for payment-level tasks that require 100% execution success rate.

• Enterprise knowledge work and document analysis: The combination of long context + file upload + extended thinking makes Claude suitable for handling long text-intensive work - contract review (entering hundreds of pages of contract terms at once for multiple rounds of questions and answers), technical document compliance check (cross-referencing policy documents with corresponding technology implementation documents), industry research report review (compare the conclusions and data sources of multiple market analysis reports). Hidden benefits: Long context not only eliminates the trouble of block processing, but also reduces the second inquiry caused by "cross-block information loss" - the completion rate of a single interaction is increased, which indirectly reduces the number of API calls.

• Financial, Legal and Medical Professional Scenarios: Anthropic publishes solutions pages specifically for these regulated industries. Claude's typical task in a financial scenario is financial report interpretation - more than 100 pages of quarterly reports are fed into Claude, who is asked to extract key financial indicators, identify abnormal trends and generate summaries. In legal scenarios, Claude can assist in legal document review—cross-referencing changes in terms between different contract versions and flagging wording with legal risks. Boundary of human-machine collaboration: Key financial decisions and legal conclusions must be reviewed by a licensed professional - Claude's output should be used as a "first draft summary" or "problem discovery tool" and is not a substitute for professional judgment.

• Security Operations and Threat Analysis: Claude Security and Project Glasswing for security teams. Typical tasks include: security log analysis (identifying suspicious patterns from massive logs), penetration testing assistance (analyzing known vulnerability patterns in the code base), and compliance audit preparation (translating policy requirements into specific configuration check items). Engineering Tips: Security scenarios are extremely sensitive to false positive rates. It is recommended to verify Claude's detection rate and false positive rate on a small-scale data set first, and then expand to production after confirming that it is acceptable.

Boundary of human-machine collaboration (productivity scenario)

Rules	Degree of automation	Manual confirmation points
Code generation and cross-file refactoring	100% automatic diff generation	Diff must be reviewed before merging
Test case generation	100% automated	Review boundary condition coverage
Document summary and knowledge Q&A	100% automatic output possible	Key terms require manual review
Business process automation (Computer Use)	Automated execution	Confirmation points for irreversible operations such as payment, deletion, and publishing
Contract review and risk flagging	Potential risks can be automatically flagged	Legal conclusions must be reviewed by a licensed professional
Customer support (standard Q&A)	Can be 100% automated	Difficulties can be upgraded to manual work
Financial analysis and report generation	Can automatically generate first draft	Key data and conclusions need to be reviewed by licensed financial personnel

Applicable groups of Claude

Claude's user stratification can be divided into two dimensions: "Depth of Capability Requirements × Compliance Sensitivity":

• Individual professional users (writers, researchers, students): The Free package can meet daily needs such as writing assistance, literature review, language translation, etc. The additional value of the Pro package is Claude Code (if you also do light coding), Projects (knowledge space) and Research (in-depth research mode). Not suitable for boundaries: Budget-sensitive users will find that competing products provide more generous free quotas; users with strong needs for multi-modal generation (such as creators who need to continuously generate images and videos) need to use other tools.

• Developer and Software Engineer: The combination of Claude Code + Sonnet/Opus is the core value. Using Claude Code in IDEs and terminals can effectively improve coding efficiency - tasks such as test generation, code interpretation, cross-file reconstruction, log analysis, etc. are changed from manual execution to natural language driven. Prerequisite: You need to be familiar with the working mode of Claude Code (Agent in the terminal, not the GUI dialog box), and be willing to partially transfer the decision-making power of the coding workflow to AI. It is not suitable for developers who do not trust AI-generated code at all - the value of Claude Code is based on the workflow of "Generate → Review → Merge". Skipping review will increase technical debt.

• Product & Technology Manager (CTO, VP Engineering): Evaluate Claude's ROI as a team development assistant. Core concerns: Claude Code Enterprise's audit and control capabilities, the expansion cost of API calls (token consumption estimate from POC to production scale), and the impact of model version switching on the compatibility of production services. Judgment Framework: If the core value of the team lies in software quality and code maintenance efficiency, Claude's coding agent ability is worth investing in; if the core value of the team lies in rapid prototyping and creative realization, AI tools that focus more on multi-modal capabilities may be more suitable.

• Enterprise Compliance and Procurement Team: Pay attention to Claude's security governance system (RSP, System Card, Constitution), compliance certification (HIPAA-ready, SOC2 terms need to be confirmed in the contract), data residency options (US-only inference, cloud platform region selection), and the enterprise version's organizational-level control capabilities (SCIM, Audit Logs, Skills whitelist). Key verification items: Before purchasing, confirm with the Anthropic business team the coverage of specific compliance certification (whether it is "platform certification" or "model certification"), as well as the data deletion clauses and audit cooperation obligations in the enterprise contract.

• Regulated Industries (Financial, Legal, Healthcare): Anthropic has published solutions pages for these industries, but industry-specific compliance requirements vary by region and regulator. Prerequisites for implementation: After evaluation and confirmation by the compliance team, priority should be given to access through cloud platform channels in order to utilize the existing compliance framework. It is recommended to pilot it in internal analysis scenarios (such as internal document search, compliance policy Q&A) first, and then carefully expand to customer-facing scenarios (such as customer support, contract generation).

• Scenarios that are not suitable or require additional conditions:

  • Users located in unsupported regions: Mainland China and other regions cannot directly access claude.ai. The compliance path is to call the API in the compliance area through a cloud account with AWS Bedrock, Vertex AI, or Microsoft Foundry. If individual users do not have an enterprise cloud account, the actual usage threshold is higher.
  • Severe multi-modal generation requirements: Claude's image understanding capabilities are available, but image and video generation are not its main capabilities. Scenarios requiring image/video AI generation should consider incorporating professional multi-modal tools.
  • High-frequency and low-latency real-time interaction: Claude's extended thinking mode has a high first-word delay. Scenarios with extremely high real-time requirements, such as customer service chats and game NPC conversations, need to be tested and confirmed to be acceptable.

Summary and Outlook

Claude is not an AI universal tool that tries to cover all the needs of everyone, but has established clear differentiated advantages on the three lines of "deep reasoning + coding agent + security compliance".

Core Competencies: The three-level model stratification of Opus / Sonnet / Haiku provides users with a clear "capability-cost" selection pedigree, and the hybrid reasoning mechanism allows the same model to adapt to different complexity requirements. Claude Code extends the coding agent from the conversational interaction paradigm to the asynchronous collaborator mode, and the Computer Use and MCP protocols build a standard framework for agent execution and tool connection. The engineering depth of the security governance system (RSP, System Card, Constitution) is leading in the AI ​​industry, providing an auditable and transparent basis for adoption by regulated industries. A multi-cloud access strategy (AWS/GCP/Azure) reduces the risk of vendor lock-in for enterprise procurement.

Current limitations and uncertainties: Claude faces the problem of limited available areas in the consumer market, and the threshold for Chinese users and individual users in non-supported areas is higher. Image/video generation is not within the scope of Claude's main capabilities, and multi-modal capabilities focus on understanding. The API cost is somewhere between the open source model and the flagship closed source model - not the cheapest option, but excellent value for money for coding/agent scenarios. The pricing of the enterprise version is not public, and enterprise buyers need to negotiate with the business team to confirm the specific terms. Claude does not open source model weights, and enterprises cannot control inference costs through self-hosting.

Follow-up observation points:

• The version iteration rhythm of the three lines of Opus / Sonnet / Haiku - whether the "Agent/Coding" theme of Sonnet 4.5 is a continuation of the subsequent main line
• Claude Code's enterprise journey - whether deep native integration can be achieved in mainstream IDEs such as VS Code and JetBrains
• Computer Use's extension to non-browser GUI automation - whether it will support mobile operation or desktop multi-application collaboration
• Ecological adoption of MCP protocol - whether it can become the de facto standard for AI Agent tool connection
• Anthropic’s compliance expansion in Asia Pacific – will it increase regional coverage of direct services

Procurement and Adoption Risk Assessment: For individual developers and technical teams, a Pro subscription or API pay-as-you-go is a low-risk starting point - there is no long-term contract binding, and you can evaluate Claude's effectiveness in your own scenarios in actual use. For medium and large enterprises, it is recommended to conduct a 1-3 month POC on non-critical paths (internal knowledge management, development assistance, document automation) to obtain actual token consumption data and quality feedback, and then apply for dedicated capacity discounts and enterprise contracts from the Anthropic business team. In regulated industries, compliance teams need to confirm specific HIPAA-ready and SOC2 coverage before purchasing, and evaluate how data residency provisions match local regulatory requirements when accessed through cloud platforms. Since Claude does not open source model weights, an enterprise's cost elasticity and migration flexibility entirely depend on the terms of the API contract - it is recommended that the advance notice period for model version switching and the aftercare support for terminating services be clearly stated in the contract. For budget-sensitive long-tail scenarios (such as large-scale content review, batch text classification), the Haiku series combined with Prompt Caching can be used as a cost control solution, but it still needs to be compared with competing products with more cost advantages such as DeepSeek and GLM for ROI comparison.

Related tools: deepseek, ChatGPT

Version Info

• Claude 2026 continuous iteration version ：Claude is a continuously iterative cloud product and API service. The official will update Opus, Sonnet, Haiku, Claude Code, connectors and enterprise capabilities on the Claude, Pricing, Docs and News pages; the specific model name, context, price and available regions are subject to the official real-time page. （~2026-07）
• Claude Sonnet 4.5 ：The milestone version of Sonnet series focuses on the stability of Agent, coding and computer use, and expands knowledge in fields such as finance and network security. （2025-09-29）
• Claude Opus 4.1 ：A direct upgrade to Opus 4, improving accuracy and multi-step reasoning performance in real coding and Agent tasks. （2025-08-05）
• Claude Opus 4 ：The first flagship of the Claude 4 series, Claude Code allows Claude Code to perform long-term coding tasks in the background for the first time. （2025-05-22）
• Claude Sonnet 4 ：Sonnet 4 is an overall improvement based on Sonnet 3.7, especially encoding, and is positioned for cost-effective production workloads. （2025-05-22）
• Claude Sonnet 3.7 ：Claude's first hybrid inference model, and subsequently launched Claude Code, launching a coding Agent product line for developers. （2025-02-24）
• Claude Haiku 3.5 ：The generational jump of the Haiku series surpasses the previous generation Opus 3 in many benchmarks, maintaining Haiku's consistent speed and cost advantages. （2024-10-22）