Model Comparison

DeepSeek R1 Zero vs Llama 4 ScoutWhich is better in 2026?

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Verdict: DeepSeek R1 Zero vs Llama 4 Scout — which is better?

DeepSeek R1 Zero (by DeepSeek) and Llama 4 Scout (by Meta) 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 Zero outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Llama 4 Scout is better at 0 benchmarks. DeepSeek R1 Zero significantly outperforms across most benchmarks.

Choose DeepSeek R1 Zero if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks

Choose Llama 4 Scout if…

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

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek R1 Zero outperforms in 2 benchmarks (GPQA, LiveCodeBench), while Llama 4 Scout is better at 0 benchmarks.

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Thu Jun 11 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

562.0B diff

DeepSeek R1 Zero has 562.0B more parameters than Llama 4 Scout, making it 515.6% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Meta
Llama 4 Scout
109.0Bparameters
671.0B
DeepSeek R1 Zero
109.0B
Llama 4 Scout

Context Window

Maximum input and output token capacity

Only Llama 4 Scout specifies input context (10,000,000 tokens). Only Llama 4 Scout specifies output context (10,000,000 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Meta
Llama 4 Scout
Input10,000,000 tokens
Output10,000,000 tokens
Thu Jun 11 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 4 Scout supports multimodal inputs, whereas DeepSeek R1 Zero does not.

Llama 4 Scout can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Zero

Text
Images
Audio
Video

Llama 4 Scout

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Llama 4 Scout uses Llama 4 Community License Agreement.

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

DeepSeek R1 Zero

MIT

Open weights

Llama 4 Scout

Llama 4 Community License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Zero was released on 2025-01-20, while Llama 4 Scout was released on 2025-04-05.

Llama 4 Scout is 3 months newer than DeepSeek R1 Zero.

DeepSeek R1 Zero

Jan 20, 2025

1.4 years ago

Llama 4 Scout

Apr 5, 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

Higher GPQA score (73.3% vs 57.2%)
Higher LiveCodeBench score (50.0% vs 32.8%)
Larger context window (10,000,000 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Zero
Meta
Llama 4 Scout

FAQ

Common questions about DeepSeek R1 Zero vs Llama 4 Scout.

Which is better, DeepSeek R1 Zero or Llama 4 Scout?

DeepSeek R1 Zero significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and Llama 4 Scout 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 4 Scout in benchmarks?

DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Llama 4 Scout scores DocVQA: 94.4%, MGSM: 90.6%, ChartQA: 88.8%, MMLU: 79.6%, MMLU-Pro: 74.3%.

What are the context window sizes for DeepSeek R1 Zero and Llama 4 Scout?

DeepSeek R1 Zero supports an unknown number of tokens and Llama 4 Scout supports 10.0M 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 4 Scout?

Key differences include multimodal support (no vs yes), licensing (MIT vs Llama 4 Community License Agreement). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek R1 Zero and Llama 4 Scout?

DeepSeek R1 Zero is developed by DeepSeek and Llama 4 Scout is developed by Meta.