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DeepSeek-V2.5 vs Qwen2 7B Instruct

DeepSeek-V2.5 leads the LLM Stats Score 8.4 to -4.3.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V2.5 leads the overall LLM Stats Score 8.4 to -4.3, ranking #270 overall.

In the 6 individual benchmarks reported for both models, DeepSeek-V2.5 wins 6; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V2.5

  • overall performance matters — it scores 8.4 and ranks #270 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 6 of 6 exact shared results

Choose Qwen2 7B Instruct

  • you want the most recent training data — it shipped Jul 2024

At a glance

The differences that matter most.

Core performance indexes
8.4
#270
-4.3
#336
8.4
#263
-4.0
#327
6.5
#183
1.0
#228
Cost, coverage & limits
Benchmark wins
6 of 6
0 of 6
Input price
$0.14 / M
— / M
Output price
$0.28 / M
— / M
Context window
8,192

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V2.5
Qwen2 7B Instruct
14.4#212
-1.1#294
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for DeepSeek-V2.5 · 14 for Qwen2 7B Instruct

6 shared

DeepSeek-V2.5 outperforms in 6 benchmarks (AlignBench, GSM8k, HumanEval, MATH, MMLU, MT-Bench), while Qwen2 7B Instruct is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Mon Sep 07 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

228.4B diff

DeepSeek-V2.5 has 228.4B more parameters than Qwen2 7B Instruct, making it 2997.1% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
7.6Bparameters
236.0B
DeepSeek-V2.5
7.6B
Qwen2 7B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen2 7B Instruct
Input- tokens
Output- tokens
Mon Sep 07 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, 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-V2.5

deepseek

Open weights

Qwen2 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Qwen2 7B Instruct was released on 2024-07-23.

Qwen2 7B Instruct is 3 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.3 years ago

Qwen2 7B Instruct

Jul 23, 2024

2.1 years ago

2mo newer

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

Judge for yourself.

Run your own prompts against DeepSeek-V2.5 and Qwen2 7B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V2.5
✓ Preferred
Qwen2 7B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V2.5 vs Qwen2 7B Instruct.

Which is better, DeepSeek-V2.5 or Qwen2 7B Instruct?

DeepSeek-V2.5 leads the LLM Stats Score 8.4 to -4.3. DeepSeek-V2.5 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 capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V2.5 compare to Qwen2 7B Instruct in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Qwen2 7B Instruct scores MT-Bench: 84.1%, GSM8k: 82.3%, HumanEval: 79.9%, C-Eval: 77.2%, AlignBench: 72.1%.

What are the context window sizes for DeepSeek-V2.5 and Qwen2 7B Instruct?

DeepSeek-V2.5 supports 8K 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.

What are the main differences between DeepSeek-V2.5 and Qwen2 7B Instruct?

Key differences include LLM Stats Score (8.4 vs -4.3), licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V2.5 and Qwen2 7B Instruct?

DeepSeek-V2.5 is developed by DeepSeek and Qwen2 7B Instruct is developed by Alibaba Cloud / Qwen Team.