Model Comparison

DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V3 0324

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while DeepSeek-V3 0324 is better at 4 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500).

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Sat May 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

669.2B diff

DeepSeek-V3 0324 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 0324
671.0Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
671.0B
DeepSeek-V3 0324

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Sat May 16 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while DeepSeek-V3 0324 uses MIT + Model License (Commercial use allowed).

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-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while DeepSeek-V3 0324 was released on 2025-03-25.

DeepSeek-V3 0324 is 2 months newer than DeepSeek R1 Distill Qwen 1.5B.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.3 years ago

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

2mo newer

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 (163,840 tokens)
Higher AIME 2024 score (59.4% vs 52.7%)
Higher GPQA score (68.4% vs 33.8%)
Higher LiveCodeBench score (49.2% vs 16.9%)
Higher MATH-500 score (94.0% vs 83.9%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
DeepSeek
DeepSeek-V3 0324

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V3 0324.

Which is better, DeepSeek R1 Distill Qwen 1.5B or DeepSeek-V3 0324?

DeepSeek-V3 0324 significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 1.5B is made by DeepSeek and DeepSeek-V3 0324 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 0324 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 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%.

What are the context window sizes for DeepSeek R1 Distill Qwen 1.5B and DeepSeek-V3 0324?

DeepSeek R1 Distill Qwen 1.5B supports an unknown number of tokens and DeepSeek-V3 0324 supports 164K 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-V3 0324?

Key differences include licensing (MIT vs MIT + Model License (Commercial use allowed)). See the full comparison above for benchmark-by-benchmark results.