Model Comparison

DeepSeek R1 Distill Qwen 14B vs DeepSeek-V2.5Which is better in 2026?

Comparing DeepSeek R1 Distill Qwen 14B and DeepSeek-V2.5 across benchmarks, pricing, and capabilities.

Verdict: DeepSeek R1 Distill Qwen 14B vs DeepSeek-V2.5 — which is better?

DeepSeek R1 Distill Qwen 14B (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 14B 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

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 14B and DeepSeek-V2.5don'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

221.2B diff

DeepSeek-V2.5 has 221.2B more parameters than DeepSeek R1 Distill Qwen 14B, making it 1494.6% larger.

DeepSeek
DeepSeek R1 Distill Qwen 14B
14.8Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
14.8B
DeepSeek R1 Distill Qwen 14B
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 14B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Mon Jun 29 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 14B 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 14B

MIT

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 14B was released on 2025-01-20, while DeepSeek-V2.5 was released on 2024-05-08.

DeepSeek R1 Distill Qwen 14B is 9 months newer than DeepSeek-V2.5.

DeepSeek R1 Distill Qwen 14B

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

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek R1 Distill Qwen 14B and DeepSeek-V2.5 side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 14B
✓ Preferred
DeepSeek-V2.5
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 14B
DeepSeek
DeepSeek-V2.5

FAQ

Common questions about DeepSeek R1 Distill Qwen 14B vs DeepSeek-V2.5.

Which is better, DeepSeek R1 Distill Qwen 14B or DeepSeek-V2.5?

DeepSeek R1 Distill Qwen 14B (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 14B compare to DeepSeek-V2.5 in benchmarks?

DeepSeek R1 Distill Qwen 14B scores MATH-500: 93.9%, AIME 2024: 80.0%, GPQA: 59.1%, LiveCodeBench: 53.1%. 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 14B and DeepSeek-V2.5?

DeepSeek R1 Distill Qwen 14B 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 14B and DeepSeek-V2.5?

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

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