Model Comparison

DeepSeek-V2.5 vs DeepSeek R1 Distill Qwen 7B

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

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

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

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 11 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
DeepSeek
DeepSeek R1 Distill Qwen 7B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

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

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
DeepSeek
DeepSeek R1 Distill Qwen 7B
Input- tokens
Output- tokens
Sat Apr 11 2026 • llm-stats.com

License

Usage and distribution terms

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

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

DeepSeek-V2.5

deepseek

Open weights

DeepSeek R1 Distill Qwen 7B

MIT

Open weights

Release Timeline

When each model was launched

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

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

DeepSeek-V2.5

May 8, 2024

1.9 years ago

DeepSeek R1 Distill Qwen 7B

Jan 20, 2025

1.2 years ago

8mo 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

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Key Takeaways

DeepSeek
Larger context window (8,192 tokens)
DeepSeek

Detailed Comparison

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

FAQ

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

DeepSeek-V2.5 (DeepSeek) and DeepSeek R1 Distill Qwen 7B (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. DeepSeek R1 Distill Qwen 7B scores MATH-500: 92.8%, AIME 2024: 83.3%, GPQA: 49.1%, LiveCodeBench: 37.6%.
DeepSeek-V2.5 supports 8K tokens and DeepSeek R1 Distill Qwen 7B 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 (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.