Model Comparison

Claude 3.7 Sonnet vs DeepSeek R1 Zero

Claude 3.7 Sonnet shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Claude 3.7 Sonnet outperforms in 2 benchmarks (GPQA, MATH-500), while DeepSeek R1 Zero is better at 1 benchmark (AIME 2024).

Claude 3.7 Sonnet shows notably better performance in the majority of benchmarks.

Mon May 04 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Claude 3.7 Sonnet specifies input context (200,000 tokens). Only Claude 3.7 Sonnet specifies output context (128,000 tokens).

Anthropic
Claude 3.7 Sonnet
Input200,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Mon May 04 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Claude 3.7 Sonnet supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Claude 3.7 Sonnet can handle both text and other forms of data like images, making it suitable for multimodal applications.

Claude 3.7 Sonnet

Text
Images
Audio
Video

DeepSeek R1 Zero

Text
Images
Audio
Video

License

Usage and distribution terms

Claude 3.7 Sonnet is licensed under a proprietary license, while DeepSeek R1 Zero uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Claude 3.7 Sonnet

Proprietary

Closed source

DeepSeek R1 Zero

MIT

Open weights

Release Timeline

When each model was launched

Claude 3.7 Sonnet was released on 2025-02-24, while DeepSeek R1 Zero was released on 2025-01-20.

Claude 3.7 Sonnet is 1 month newer than DeepSeek R1 Zero.

Claude 3.7 Sonnet

Feb 24, 2025

1.2 years ago

1mo newer
DeepSeek R1 Zero

Jan 20, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Anthropic
Larger context window (200,000 tokens)
Supports multimodal inputs
Higher GPQA score (84.8% vs 73.3%)
Higher MATH-500 score (96.2% vs 95.9%)
DeepSeek
Has open weights
Higher AIME 2024 score (86.7% vs 80.0%)
AnthropicClaude 3.7 Sonnet
DeepSeekDeepSeek R1 Zero
Compare in Playground

Detailed Comparison

AI Model Comparison Table
Feature
Anthropic
Claude 3.7 Sonnet
DeepSeek
DeepSeek R1 Zero

FAQ

Common questions about Claude 3.7 Sonnet vs DeepSeek R1 Zero.

Which is better, Claude 3.7 Sonnet or DeepSeek R1 Zero?

Claude 3.7 Sonnet shows notably better performance in the majority of benchmarks. Claude 3.7 Sonnet is made by Anthropic and DeepSeek R1 Zero is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Claude 3.7 Sonnet compare to DeepSeek R1 Zero in benchmarks?

Claude 3.7 Sonnet scores MATH-500: 96.2%, IFEval: 93.2%, MMMLU: 86.1%, GPQA: 84.8%, TAU-bench Retail: 81.2%. DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%.

What are the context window sizes for Claude 3.7 Sonnet and DeepSeek R1 Zero?

Claude 3.7 Sonnet supports 200K tokens and DeepSeek R1 Zero supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Claude 3.7 Sonnet and DeepSeek R1 Zero?

Key differences include multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Claude 3.7 Sonnet and DeepSeek R1 Zero?

Claude 3.7 Sonnet is developed by Anthropic and DeepSeek R1 Zero is developed by DeepSeek.