Model Comparison

DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V3 0324Which is better in 2026?

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Verdict: DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V3 0324 — which is better?

DeepSeek R1 Distill Qwen 1.5B (by DeepSeek) and DeepSeek-V3 0324 (by DeepSeek) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

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.

Choose DeepSeek R1 Distill Qwen 1.5B if…

  • you are already invested in the DeepSeek ecosystem

Choose DeepSeek-V3 0324 if…

  • you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
  • you want the most recent training data — it shipped Mar 2025
Want to compare interactively?Try the playground

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 Jun 06 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 Jun 06 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

1.4 years ago

DeepSeek-V3 0324

Mar 25, 2025

1.2 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.

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