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DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V2.5

DeepSeek-V2.5 leads the LLM Stats Score 8.4 to -2.7.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek-V2.5 leads the overall LLM Stats Score 8.4 to -2.7, ranking #266 overall.

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

Choose DeepSeek R1 Distill Qwen 1.5B

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

Choose DeepSeek-V2.5

  • overall performance matters — it scores 8.4 and ranks #266 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes

At a glance

The differences that matter most.

DeepSeek R1 Distill Qwen 1.5B
DeepSeek
DeepSeek-V2.5
DeepSeek
Core performance indexes
LLM Stats Score
-2.7
#326
8.4
#266
Reasoning
-2.4
#316
8.5
#260
Coding
-4.5
#246
6.5
#179
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 1.5B
DeepSeek-V2.5
Math
5.7#261
14.4#211
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Distill Qwen 1.5B · 15 for DeepSeek-V2.5

No common benchmarks found

DeepSeek R1 Distill Qwen 1.5B 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

234.2B diff

DeepSeek-V2.5 has 234.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 13158.4% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
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 1.5B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Wed Sep 02 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 1.5B 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 1.5B

MIT

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while DeepSeek-V2.5 was released on 2024-05-08.

DeepSeek R1 Distill Qwen 1.5B is 9 months newer than DeepSeek-V2.5.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.6 years ago

8mo newer
DeepSeek-V2.5

May 8, 2024

2.3 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 1.5B and DeepSeek-V2.5 side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 1.5B
✓ Preferred
DeepSeek-V2.5
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V2.5.

Which is better, DeepSeek R1 Distill Qwen 1.5B or DeepSeek-V2.5?

DeepSeek-V2.5 leads the LLM Stats Score 8.4 to -2.7. DeepSeek R1 Distill Qwen 1.5B 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 1.5B compare to DeepSeek-V2.5 in benchmarks?

DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. 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 1.5B and DeepSeek-V2.5?

DeepSeek R1 Distill Qwen 1.5B 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 1.5B and DeepSeek-V2.5?

Key differences include LLM Stats Score (-2.7 vs 8.4), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.

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