Technology comparison

Claude 3.5 Sonnet vs Claude 3.7 Sonnet: models, context & API pricing

Choose Claude 3.5 Sonnet for stable, cost-sensitive workloads where its proven reliability and lower pricing tier matter. Choose Claude 3.7 Sonnet for complex reasoning, coding, and hybrid extended-thinking tasks where its improved benchmark performance and adaptive reasoning justify a possible higher cost. Verify current pricing and availability, as both are subject to change.

Technical context and trade-offs

These differences are drawn directly from the comparison criteria below.

Context Window

Claude 3.5 Sonnet: Claude 3.5 Sonnet offers a 200K token context window according to Anthropic's published model documentation. This is sufficient for long documents, codebases, and multi-turn conversations, though very large inputs may require chunking or retrieval augmentation. The exact limit should be confirmed against the current Anthropic API documentation, as it may vary by model version and access tier.

Claude 3.7 Sonnet: Claude 3.7 Sonnet also provides a 200K token context window, matching its predecessor in raw input capacity. However, with extended thinking enabled, the effective context available for output may be reduced because thinking tokens count toward the total. Users should verify the exact context handling in Anthropic's documentation for the specific API version and thinking budget configuration.

Benchmark Performance (MMLU and HumanEval)

Claude 3.5 Sonnet: Anthropic has published benchmark results for Claude 3.5 Sonnet, including scores on MMLU and HumanEval, though exact numbers vary by evaluation setup and are version-sensitive. These results show strong general knowledge and coding ability, but they should be compared cautiously because different prompting and evaluation harnesses can produce different outcomes. For the most current and comparable figures, consult Anthropic's official model cards and announcements.

Claude 3.7 Sonnet: Claude 3.7 Sonnet has reported improvements over 3.5 Sonnet on several benchmarks, including MMLU and HumanEval, according to Anthropic's release materials. The gains are often attributed to enhanced reasoning and coding capabilities, but published scores depend on the specific evaluation protocol and whether extended thinking is enabled. Users should verify the latest benchmark numbers from Anthropic and independent evaluations before drawing conclusions.

Quick verdictThe bottom line

Claude 3.5 SonnetClaude 3.7 SonnetExplore the detailed comparison

Scores by criterion

Performance50–50 (2 criteria)

Ease of useNo direct evidence in the criteria

EcosystemNo direct evidence in the criteria

PopularityNo direct evidence in the criteria

Claude 3.5 SonnetClaude 3.7 Sonnet

Scores reflect wins in matching criteria; ties count as half a point.

Technical feature matrix

Criterion	Claude 3.5 Sonnet	Claude 3.7 Sonnet	Edge
Context Window	Claude 3.5 Sonnet offers a 200K token context window according to Anthropic's published model documentation. This is sufficient for long documents, codebases, and multi-turn conversations, though very large inputs may require chunking or retrieval augmentation. The exact limit should be confirmed against the current Anthropic API documentation, as it may vary by model version and access tier.	Claude 3.7 Sonnet also provides a 200K token context window, matching its predecessor in raw input capacity. However, with extended thinking enabled, the effective context available for output may be reduced because thinking tokens count toward the total. Users should verify the exact context handling in Anthropic's documentation for the specific API version and thinking budget configuration.	Comparable
Benchmark Performance (MMLU and HumanEval)	Anthropic has published benchmark results for Claude 3.5 Sonnet, including scores on MMLU and HumanEval, though exact numbers vary by evaluation setup and are version-sensitive. These results show strong general knowledge and coding ability, but they should be compared cautiously because different prompting and evaluation harnesses can produce different outcomes. For the most current and comparable figures, consult Anthropic's official model cards and announcements.	Claude 3.7 Sonnet has reported improvements over 3.5 Sonnet on several benchmarks, including MMLU and HumanEval, according to Anthropic's release materials. The gains are often attributed to enhanced reasoning and coding capabilities, but published scores depend on the specific evaluation protocol and whether extended thinking is enabled. Users should verify the latest benchmark numbers from Anthropic and independent evaluations before drawing conclusions.	Claude 3.7 Sonnet
API Pricing (per 1M Input/Output Tokens)	Claude 3.5 Sonnet's API pricing is generally positioned as a mid-tier option, with per-token rates that are lower than some premium models. Exact input and output token prices are subject to change and may vary by region or contract; for example, Anthropic has historically listed input pricing around $3 per million tokens and output around $15 per million tokens, but these figures must be verified against the current official pricing page. Volume discounts and enterprise agreements can also affect effective cost.	Claude 3.7 Sonnet is typically priced at a similar or slightly higher tier than 3.5 Sonnet, and extended thinking may increase output token usage because thinking tokens are billed. Published rates have been in the same range as 3.5 Sonnet for standard usage, but the effective cost per request can be higher when extended thinking is enabled. Always check Anthropic's current pricing documentation for the latest per-million-token rates and any thinking-specific billing details.	Claude 3.5 Sonnet
Latency and Response Speed	Claude 3.5 Sonnet is designed for low-latency responses in standard mode, making it suitable for interactive applications and real-time chat. Actual latency depends on factors such as prompt length, output size, server load, and network conditions, so no single figure applies universally. Anthropic does not publish guaranteed latency SLAs for all tiers, so users should benchmark in their own environment if latency is critical.	Claude 3.7 Sonnet offers similar latency to 3.5 Sonnet in standard mode, but enabling extended thinking introduces additional processing time because the model generates internal reasoning tokens before responding. This can significantly increase response time for complex queries, though the trade-off may be worthwhile for tasks requiring deeper reasoning. As with any API, real-world latency varies with workload and configuration, so empirical testing is recommended.	Claude 3.5 Sonnet
Model Access and Open/Closed Availability	Claude 3.5 Sonnet is a closed-source model available via Anthropic's API, Amazon Bedrock, and Google Cloud Vertex AI, with access governed by Anthropic's usage policies and commercial terms. It is not available as open weights, so users cannot self-host or modify the model. Availability may differ by region and cloud provider, and some features may require specific access approvals.	Claude 3.7 Sonnet is also a closed-source model offered through Anthropic's API and major cloud platforms, including Amazon Bedrock and Google Cloud Vertex AI. Like 3.5 Sonnet, it is not open-weight, and access is subject to Anthropic's terms and regional availability. The extended thinking feature may have additional access requirements or be rolled out gradually, so users should check the provider's documentation for current availability.	Comparable
Practical Use Cases	Claude 3.5 Sonnet excels at general-purpose tasks such as text generation, summarization, customer support automation, and code assistance where low latency and cost efficiency are important. Its stable performance and broad availability make it a solid choice for production workloads that do not require advanced reasoning. It is also well-suited for educational and content-creation applications.	Claude 3.7 Sonnet is better suited for complex problem-solving, advanced coding, mathematical reasoning, and tasks that benefit from extended thinking, such as multi-step analysis and agentic workflows. The ability to toggle extended thinking allows developers to balance speed and depth, making it versatile for both quick queries and deep reasoning. However, the potential for higher token usage and latency means it may not be ideal for high-throughput, low-latency scenarios.	Claude 3.7 Sonnet
Reasoning and Extended Thinking	Claude 3.5 Sonnet does not include a dedicated extended thinking mode; it generates responses directly based on the input. This makes its behavior more predictable and simpler to integrate, but it may struggle with tasks that require extensive internal reasoning or self-correction. For many applications, its reasoning capabilities are sufficient, especially when combined with good prompting.	Claude 3.7 Sonnet introduces an extended thinking capability that allows the model to allocate additional compute to internal reasoning before producing a final answer. This can improve performance on complex tasks, but it also increases output token consumption and latency, and the thinking process may not be fully transparent. Developers can control the thinking budget, but should verify how thinking tokens are billed and whether they are exposed in the API response.	Claude 3.7 Sonnet

When to choose each option

Choose this option if… Claude 3.5 Sonnet

Choose Claude 3.5 Sonnet when the strengths described here match your project requirements. API Pricing (per 1M Input/Output Tokens): Claude 3.5 Sonnet's API pricing is generally positioned as a mid-tier option, with per-token rates that are lower than some premium models. Exact input and output token prices are subject to change and may vary by region or contract; for example, Anthropic has historically listed input pricing around $3 per million tokens and output around $15 per million tokens, but these figures must be verified against the current official pricing page. Volume discounts and enterprise agreements can also affect effective cost. Latency and Response Speed: Claude 3.5 Sonnet is designed for low-latency responses in standard mode, making it suitable for interactive applications and real-time chat. Actual latency depends on factors such as prompt length, output size, server load, and network conditions, so no single figure applies universally. Anthropic does not publish guaranteed latency SLAs for all tiers, so users should benchmark in their own environment if latency is critical.

Choose this option if… Claude 3.7 Sonnet

Choose Claude 3.7 Sonnet when the strengths described here match your project requirements. Benchmark Performance (MMLU and HumanEval): Claude 3.7 Sonnet has reported improvements over 3.5 Sonnet on several benchmarks, including MMLU and HumanEval, according to Anthropic's release materials. The gains are often attributed to enhanced reasoning and coding capabilities, but published scores depend on the specific evaluation protocol and whether extended thinking is enabled. Users should verify the latest benchmark numbers from Anthropic and independent evaluations before drawing conclusions. Practical Use Cases: Claude 3.7 Sonnet is better suited for complex problem-solving, advanced coding, mathematical reasoning, and tasks that benefit from extended thinking, such as multi-step analysis and agentic workflows. The ability to toggle extended thinking allows developers to balance speed and depth, making it versatile for both quick queries and deep reasoning. However, the potential for higher token usage and latency means it may not be ideal for high-throughput, low-latency scenarios. Reasoning and Extended Thinking: Claude 3.7 Sonnet introduces an extended thinking capability that allows the model to allocate additional compute to internal reasoning before producing a final answer. This can improve performance on complex tasks, but it also increases output token consumption and latency, and the thinking process may not be fully transparent. Developers can control the thinking budget, but should verify how thinking tokens are billed and whether they are exposed in the API response.

Technology role diagram

Option A

Claude 3.5 Sonnet

Comparison

Option B

Claude 3.7 Sonnet

Comparison

This diagram shows broad areas of use, not a complete deployment architecture.

Code examples

Claude 3.5 Sonnet

import anthropic

client = anthropic.Anthropic(api_key="YOUR_API_KEY")
response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=100,
    messages=[{"role": "user", "content": "Hello, World!"}]
)
print(response.content[0].text)

Frequently asked questions

Which model is better for coding tasks?

Claude 3.7 Sonnet generally shows improved performance on coding benchmarks like HumanEval compared to 3.5 Sonnet, and its extended thinking mode can help with complex debugging or algorithm design. However, for straightforward code generation and completion, 3.5 Sonnet remains highly capable and may be more cost-effective. The best choice depends on the complexity of your coding tasks and your budget for tokens and latency.

Is Claude 3.7 Sonnet significantly more expensive than 3.5 Sonnet?

Anthropic's published pricing for Claude 3.7 Sonnet has been in a similar range to 3.5 Sonnet for standard usage, but extended thinking can increase output token consumption, raising the effective cost per request. Prices are subject to change, so you should verify the current per-million-token rates on Anthropic's official pricing page. For high-volume applications, even small differences in token usage can impact overall cost.

Can I use extended thinking with Claude 3.7 Sonnet in all regions?

Extended thinking availability may vary by region and access tier, and it might be rolled out gradually. Anthropic's documentation should be consulted for the latest regional availability and any access requirements. If extended thinking is not available in your region, you can still use Claude 3.7 Sonnet in standard mode, which offers improvements over 3.5 Sonnet.

What is the context window for both models?

Both Claude 3.5 Sonnet and Claude 3.7 Sonnet offer a 200K token context window according to Anthropic's published specifications. However, with extended thinking enabled on 3.7 Sonnet, some of the token budget may be consumed by thinking tokens, reducing the space available for input and output. Always confirm the exact context limits in the current API documentation, as they may be updated.

Which model has lower latency?

In standard mode, both models have similar latency profiles, but Claude 3.5 Sonnet may be slightly faster because it does not have the overhead of extended thinking. Enabling extended thinking on Claude 3.7 Sonnet can significantly increase response time for complex queries. For latency-sensitive applications, you should benchmark both models in your own environment and consider using 3.5 Sonnet or 3.7 Sonnet without extended thinking.

Are these models open source?

No, both Claude 3.5 Sonnet and Claude 3.7 Sonnet are closed-source models available only through Anthropic's API and authorized cloud platforms. They are not available as open weights, so you cannot self-host or modify them. Access is governed by Anthropic's usage policies, and availability may differ by region and provider.

Which model should I choose for a production application?

For production applications that require stable, cost-effective performance and low latency, Claude 3.5 Sonnet is often a reliable choice. If your application involves complex reasoning, advanced coding, or tasks where improved accuracy justifies potentially higher token usage and latency, Claude 3.7 Sonnet with extended thinking may be preferable. Consider running a pilot with both models on your specific workloads to make an informed decision.

How do I access these models?

You can access both models via Anthropic's API, Amazon Bedrock, and Google Cloud Vertex AI, subject to your account permissions and regional availability. You will need an API key and must comply with Anthropic's usage policies. For the most current access methods and regions, refer to Anthropic's official documentation and cloud provider listings.