Model Comparison

DeepSeek R1 Zero vs Llama 3.1 405B Instruct

DeepSeek R1 Zero significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek R1 Zero outperforms in 1 benchmarks (GPQA), while Llama 3.1 405B Instruct is better at 0 benchmarks.

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Wed May 06 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

266.0B diff

DeepSeek R1 Zero has 266.0B more parameters than Llama 3.1 405B Instruct, making it 65.7% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Meta
Llama 3.1 405B Instruct
405.0Bparameters
671.0B
DeepSeek R1 Zero
405.0B
Llama 3.1 405B Instruct

Context Window

Maximum input and output token capacity

Only Llama 3.1 405B Instruct specifies input context (128,000 tokens). Only Llama 3.1 405B Instruct specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Meta
Llama 3.1 405B Instruct
Input128,000 tokens
Output128,000 tokens
Wed May 06 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Llama 3.1 405B Instruct uses Llama 3.1 Community License.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek R1 Zero

MIT

Open weights

Llama 3.1 405B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Llama 3.1 405B Instruct was released on 2024-07-23.

DeepSeek R1 Zero is 6 months newer than Llama 3.1 405B Instruct.

DeepSeek R1 Zero

Jan 20, 2025

1.3 years ago

6mo newer
Llama 3.1 405B Instruct

Jul 23, 2024

1.8 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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Higher GPQA score (73.3% vs 50.7%)
Meta
Larger context window (128,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
Meta
Llama 3.1 405B Instruct

FAQ

Common questions about DeepSeek R1 Zero vs Llama 3.1 405B Instruct.

Which is better, DeepSeek R1 Zero or Llama 3.1 405B Instruct?

DeepSeek R1 Zero significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and Llama 3.1 405B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek R1 Zero compare to Llama 3.1 405B Instruct in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Llama 3.1 405B Instruct scores ARC-C: 96.9%, GSM8k: 96.8%, API-Bank: 92.0%, Multilingual MGSM (CoT): 91.6%, HumanEval: 89.0%.

What are the context window sizes for DeepSeek R1 Zero and Llama 3.1 405B Instruct?

DeepSeek R1 Zero supports an unknown number of tokens and Llama 3.1 405B Instruct supports 128K 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 Llama 3.1 405B Instruct?

Key differences include licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Llama 3.1 405B Instruct?

DeepSeek R1 Zero is developed by DeepSeek and Llama 3.1 405B Instruct is developed by Meta.