Model Comparison

Claude 3.7 Sonnet vs DeepSeek VL2

Claude 3.7 Sonnet significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Claude 3.7 Sonnet outperforms in 1 benchmarks (MMMU), while DeepSeek VL2 is better at 0 benchmarks.

Claude 3.7 Sonnet significantly outperforms across most benchmarks.

Fri Apr 03 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Fri Apr 03 2026 • llm-stats.com
Anthropic
Claude 3.7 Sonnet
Input tokens$3.00
Output tokens$15.00
Best providerAnthropic
DeepSeek
DeepSeek VL2
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Claude 3.7 Sonnet accepts 200,000 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek VL2 can generate longer responses up to 129,280 tokens, while Claude 3.7 Sonnet is limited to 128,000 tokens.

Anthropic
Claude 3.7 Sonnet
Input200,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Fri Apr 03 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Claude 3.7 Sonnet and DeepSeek VL2 support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Claude 3.7 Sonnet

Text
Images
Audio
Video

DeepSeek VL2

Text
Images
Audio
Video

License

Usage and distribution terms

Claude 3.7 Sonnet is licensed under a proprietary license, while DeepSeek VL2 uses deepseek.

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

Claude 3.7 Sonnet

Proprietary

Closed source

DeepSeek VL2

deepseek

Open weights

Release Timeline

When each model was launched

Claude 3.7 Sonnet was released on 2025-02-24, while DeepSeek VL2 was released on 2024-12-13.

Claude 3.7 Sonnet is 2 months newer than DeepSeek VL2.

Claude 3.7 Sonnet

Feb 24, 2025

1.1 years ago

2mo newer
DeepSeek VL2

Dec 13, 2024

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

Provider Availability

Claude 3.7 Sonnet is available from Anthropic, Bedrock, Google. DeepSeek VL2 is available from Replicate.

Claude 3.7 Sonnet

anthropic logo
Anthropic
Input Price:Input: $3.00/1MOutput Price:Output: $15.00/1M
bedrock logo
AWS Bedrock
Input Price:Input: $3.00/1MOutput Price:Output: $15.00/1M
google logo
Google
Input Price:Input: $3.00/1MOutput Price:Output: $15.00/1M

DeepSeek VL2

replicate logo
Replicate
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Anthropic
Larger context window (200,000 tokens)
Higher MMMU score (75.0% vs 51.1%)
DeepSeek
Has open weights
AnthropicClaude 3.7 Sonnet
DeepSeekDeepSeek VL2
Compare in Playground

Detailed Comparison

AI Model Comparison Table
Feature
Anthropic
Claude 3.7 Sonnet
DeepSeek
DeepSeek VL2

FAQ

Common questions about Claude 3.7 Sonnet vs DeepSeek VL2

Claude 3.7 Sonnet significantly outperforms across most benchmarks. Claude 3.7 Sonnet is made by Anthropic and DeepSeek VL2 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Claude 3.7 Sonnet scores MATH-500: 96.2%, IFEval: 93.2%, MMMLU: 86.1%, GPQA: 84.8%, TAU-bench Retail: 81.2%. DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%.
Claude 3.7 Sonnet supports 200K tokens and DeepSeek VL2 supports 129K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (200K vs 129K), licensing (Proprietary vs deepseek). See the full comparison above for benchmark-by-benchmark results.
Claude 3.7 Sonnet is developed by Anthropic and DeepSeek VL2 is developed by DeepSeek.