Model Comparison

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

Comparing DeepSeek R1 Distill Qwen 1.5B and DeepSeek-V2.5 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Qwen 1.5B 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

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Mon Apr 13 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

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
Mon Apr 13 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

1.2 years ago

8mo newer
DeepSeek-V2.5

May 8, 2024

1.9 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

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Key Takeaways

DeepSeek
DeepSeek
Larger context window (8,192 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
DeepSeek
DeepSeek-V2.5

FAQ

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

DeepSeek R1 Distill Qwen 1.5B (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.
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%.
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.
Key differences include licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.