Model Comparison

DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V3.1

DeepSeek-V3.1 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while DeepSeek-V3.1 is better at 3 benchmarks (AIME 2024, GPQA, LiveCodeBench).

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Fri May 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

669.2B diff

DeepSeek-V3.1 has 669.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 37596.6% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
DeepSeek
DeepSeek-V3.1
671.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
671.0B
DeepSeek-V3.1

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.1 specifies input context (163,840 tokens). Only DeepSeek-V3.1 specifies output context (163,840 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Fri May 15 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

DeepSeek-V3.1

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while DeepSeek-V3.1 was released on 2025-01-10.

DeepSeek R1 Distill Qwen 1.5B is 0 month newer than DeepSeek-V3.1.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.3 years ago

1w newer
DeepSeek-V3.1

Jan 10, 2025

1.3 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

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Key Takeaways

DeepSeek

No standout differentiators in the data we have for this pair.

DeepSeek
Larger context window (163,840 tokens)
Higher AIME 2024 score (66.3% vs 52.7%)
Higher GPQA score (74.9% vs 33.8%)
Higher LiveCodeBench score (56.4% vs 16.9%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
DeepSeek
DeepSeek-V3.1

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V3.1.

Which is better, DeepSeek R1 Distill Qwen 1.5B or DeepSeek-V3.1?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 1.5B is made by DeepSeek and DeepSeek-V3.1 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Distill Qwen 1.5B compare to DeepSeek-V3.1 in benchmarks?

DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%.

What are the context window sizes for DeepSeek R1 Distill Qwen 1.5B and DeepSeek-V3.1?

DeepSeek R1 Distill Qwen 1.5B supports an unknown number of tokens and DeepSeek-V3.1 supports 164K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.