Model Comparison

DeepSeek R1 Distill Qwen 7B vs DeepSeek-V2.5Which is better in 2026?

Comparing DeepSeek R1 Distill Qwen 7B and DeepSeek-V2.5 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek R1 Distill Qwen 7B vs DeepSeek-V2.5 — which is better?

DeepSeek R1 Distill Qwen 7B (by DeepSeek) and DeepSeek-V2.5 (by DeepSeek) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose DeepSeek R1 Distill Qwen 7B if…

  • you want the most recent training data — it shipped Jan 2025

Choose DeepSeek-V2.5 if…

  • you want predictable pricing at $0.14/M input and $0.28/M output
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 7B and DeepSeek-V2.5 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

228.4B diff

DeepSeek-V2.5 has 228.4B more parameters than DeepSeek R1 Distill Qwen 7B, making it 2997.1% larger.

DeepSeek
DeepSeek R1 Distill Qwen 7B
7.6Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
7.6B
DeepSeek R1 Distill Qwen 7B
236.0B
DeepSeek-V2.5

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 R1 Distill Qwen 7B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Sat Jun 06 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 7B is licensed under MIT, while DeepSeek-V2.5 uses deepseek.

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

DeepSeek R1 Distill Qwen 7B

MIT

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 7B was released on 2025-01-20, while DeepSeek-V2.5 was released on 2024-05-08.

DeepSeek R1 Distill Qwen 7B is 9 months newer than DeepSeek-V2.5.

DeepSeek R1 Distill Qwen 7B

Jan 20, 2025

1.4 years ago

8mo newer
DeepSeek-V2.5

May 8, 2024

2.1 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

No standout differentiators in the data we have for this pair.

DeepSeek
Larger context window (8,192 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 7B
DeepSeek
DeepSeek-V2.5

FAQ

Common questions about DeepSeek R1 Distill Qwen 7B vs DeepSeek-V2.5.

Which is better, DeepSeek R1 Distill Qwen 7B or DeepSeek-V2.5?

DeepSeek R1 Distill Qwen 7B (DeepSeek) and DeepSeek-V2.5 (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek R1 Distill Qwen 7B compare to DeepSeek-V2.5 in benchmarks?

DeepSeek R1 Distill Qwen 7B scores MATH-500: 92.8%, AIME 2024: 83.3%, GPQA: 49.1%, LiveCodeBench: 37.6%. DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%.

What are the context window sizes for DeepSeek R1 Distill Qwen 7B and DeepSeek-V2.5?

DeepSeek R1 Distill Qwen 7B supports an unknown number of tokens and DeepSeek-V2.5 supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek R1 Distill Qwen 7B and DeepSeek-V2.5?

Key differences include licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.

Related comparisons