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DeepSeek R1 Zero vs DeepSeek-V3 0324

DeepSeek R1 Zero significantly outperforms across most benchmarks.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek R1 Zero outperforms in 4 benchmarks (AIME 2024, GPQA, LiveCodeBench, MATH-500), while DeepSeek-V3 0324 is better at 0 benchmarks. DeepSeek R1 Zero significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek R1 Zero

  • you want the strongest raw capability — it leads on 4 of 4 shared benchmarks

Choose DeepSeek-V3 0324

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

At a glance

The differences that matter most.

DeepSeek R1 Zero
DeepSeek
DeepSeek-V3 0324
DeepSeek
Benchmark wins
4 of 4
0 of 4
Input price
— / M
$0.28 / M
Output price
— / M
$1.14 / M
Context window
—
163,840
Released
Jan 2025
Mar 2025
License
MIT
MIT + Model License (Commercial use allowed)

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

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

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

0.0M diff

DeepSeek-V3 0324 has 0.0B more parameters than DeepSeek R1 Zero, making it 0.0% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
DeepSeek
DeepSeek-V3 0324
671.0Bparameters
671.0B
DeepSeek R1 Zero
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 Zero
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Tue Aug 25 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Zero 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 Zero

MIT

Open weights

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero 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 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.6 years ago

DeepSeek-V3 0324

Mar 25, 2025

1.4 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→

Judge for yourself.

Run your own prompts against DeepSeek R1 Zero and DeepSeek-V3 0324 side-by-side, then vote on the output you prefer.

DeepSeek R1 Zero
✓ Preferred
DeepSeek-V3 0324
Open in Playground

FAQ

Common questions about DeepSeek R1 Zero vs DeepSeek-V3 0324.

Which is better, DeepSeek R1 Zero or DeepSeek-V3 0324?

DeepSeek R1 Zero significantly outperforms across most benchmarks. DeepSeek R1 Zero 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 Zero compare to DeepSeek-V3 0324 in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. 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 Zero and DeepSeek-V3 0324?

DeepSeek R1 Zero 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 Zero 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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