Model Comparison

DeepSeek-V3 vs Qwen2 7B Instruct

DeepSeek-V3 significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

DeepSeek-V3 outperforms in 5 benchmarks (C-Eval, GPQA, LiveCodeBench, MMLU, MMLU-Pro), while Qwen2 7B Instruct is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Sun Mar 29 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
Sun Mar 29 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

663.4B diff

DeepSeek-V3 has 663.4B more parameters than Qwen2 7B Instruct, making it 8705.8% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
7.6Bparameters
671.0B
DeepSeek-V3
7.6B
Qwen2 7B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
Input- tokens
Output- tokens
Sun Mar 29 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Qwen2 7B Instruct uses Apache 2.0.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Qwen2 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Qwen2 7B Instruct was released on 2024-07-23.

DeepSeek-V3 is 5 months newer than Qwen2 7B Instruct.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

5mo newer
Qwen2 7B Instruct

Jul 23, 2024

1.7 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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher C-Eval score (86.5% vs 77.2%)
Higher GPQA score (59.1% vs 25.3%)
Higher LiveCodeBench score (37.6% vs 26.6%)
Higher MMLU score (88.5% vs 70.5%)
Higher MMLU-Pro score (75.9% vs 44.1%)
Alibaba Cloud / Qwen Team

Qwen2 7B Instruct

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct

FAQ

Common questions about DeepSeek-V3 vs Qwen2 7B Instruct

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Qwen2 7B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Qwen2 7B Instruct scores MT-Bench: 84.1%, GSM8k: 82.3%, HumanEval: 79.9%, C-Eval: 77.2%, AlignBench: 72.1%.
DeepSeek-V3 supports 131K tokens and Qwen2 7B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Qwen2 7B Instruct is developed by Alibaba Cloud / Qwen Team.