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DeepSeek R1 Distill Qwen 14B vs DeepSeek-V2.5

DeepSeek R1 Distill Qwen 14B and DeepSeek-V2.5 are closely matched at 10.9 and 8.1 on the LLM Stats Score.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek R1 Distill Qwen 14B and DeepSeek-V2.5 are closely matched on the overall LLM Stats Score at 10.9 and 8.1.

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

Choose DeepSeek R1 Distill Qwen 14B

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

Choose DeepSeek-V2.5

  • you want predictable pricing at $0.14/M input and $0.28/M output

At a glance

The differences that matter most.

DeepSeek R1 Distill Qwen 14B
DeepSeek
DeepSeek-V2.5
DeepSeek
Core performance indexes
LLM Stats Score
10.9
#266
8.1
#287
Reasoning
11.3
#262
8.2
#283
Coding
5.5
#204
6.3
#197
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.14 / M
Output price
— / M
$0.28 / M
Context window
—
8,192

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Distill Qwen 14B
DeepSeek-V2.5
Math
13.4#229
14.0#223
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Distill Qwen 14B · 15 for DeepSeek-V2.5

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.

Human preference

Blind head-to-head votes and playground preference scores

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
Sun Sep 27 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

1.7 years ago

8mo newer
DeepSeek-V2.5

May 8, 2024

2.4 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→

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

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 and DeepSeek-V2.5 are closely matched on the LLM Stats Score at 10.9 and 8.1. DeepSeek R1 Distill Qwen 14B is made by DeepSeek and DeepSeek-V2.5 is made by DeepSeek. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

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 LLM Stats Score (10.9 vs 8.1), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.

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