Model Comparison

DeepSeek R1 Distill Llama 70B vs DeepSeek R1 ZeroWhich is better in 2026?

DeepSeek R1 Zero has a slight edge in benchmark performance.

Verdict: DeepSeek R1 Distill Llama 70B vs DeepSeek R1 Zero — which is better?

DeepSeek R1 Distill Llama 70B (by DeepSeek) and DeepSeek R1 Zero (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 Llama 70B outperforms in 1 benchmarks (LiveCodeBench), while DeepSeek R1 Zero is better at 2 benchmarks (GPQA, MATH-500). DeepSeek R1 Zero has a slight edge in benchmark performance.

Choose DeepSeek R1 Distill Llama 70B if…

  • you want predictable pricing at $0.10/M input and $0.40/M output

Choose DeepSeek R1 Zero if…

  • you want the strongest raw capability — it leads on 3 of 4 shared benchmarks

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek R1 Distill Llama 70B outperforms in 1 benchmarks (LiveCodeBench), while DeepSeek R1 Zero is better at 2 benchmarks (GPQA, MATH-500).

DeepSeek R1 Zero has a slight edge in benchmark performance.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

600.4B diff

DeepSeek R1 Zero has 600.4B more parameters than DeepSeek R1 Distill Llama 70B, making it 850.4% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
DeepSeek
DeepSeek R1 Zero
671.0Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
671.0B
DeepSeek R1 Zero

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Llama 70B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Tue Jul 21 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 Llama 70B

MIT

Open weights

DeepSeek R1 Zero

MIT

Open weights

Release Timeline

When each model was launched

Both models were released on 2025-01-20.

They likely represent similar generations of model development.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.5 years ago

DeepSeek R1 Zero

Jan 20, 2025

1.5 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
Larger context window (128,000 tokens)
Higher LiveCodeBench score (57.5% vs 50.0%)
DeepSeek
Higher GPQA score (73.3% vs 65.2%)
Higher MATH-500 score (95.9% vs 94.5%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek R1 Distill Llama 70B and DeepSeek R1 Zero side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Llama 70B
✓ Preferred
DeepSeek R1 Zero
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Llama 70B
DeepSeek
DeepSeek R1 Zero

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs DeepSeek R1 Zero.

Which is better, DeepSeek R1 Distill Llama 70B or DeepSeek R1 Zero?

DeepSeek R1 Zero has a slight edge in benchmark performance. DeepSeek R1 Distill Llama 70B is made by DeepSeek and DeepSeek R1 Zero 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 Llama 70B compare to DeepSeek R1 Zero in benchmarks?

DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%.

What are the context window sizes for DeepSeek R1 Distill Llama 70B and DeepSeek R1 Zero?

DeepSeek R1 Distill Llama 70B supports 128K tokens and DeepSeek R1 Zero supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Related comparisons