Model Comparison

DeepSeek R1 Zero vs Llama 4 Maverick

DeepSeek R1 Zero significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

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

DeepSeek R1 Zero significantly outperforms across most benchmarks.

Tue Apr 07 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 07 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Zero
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Meta
Llama 4 Maverick
Input tokens$0.17
Output tokens$0.60
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

271.0B diff

DeepSeek R1 Zero has 271.0B more parameters than Llama 4 Maverick, making it 67.8% larger.

DeepSeek
DeepSeek R1 Zero
671.0Bparameters
Meta
Llama 4 Maverick
400.0Bparameters
671.0B
DeepSeek R1 Zero
400.0B
Llama 4 Maverick

Context Window

Maximum input and output token capacity

Only Llama 4 Maverick specifies input context (1,000,000 tokens). Only Llama 4 Maverick specifies output context (1,000,000 tokens).

DeepSeek
DeepSeek R1 Zero
Input- tokens
Output- tokens
Meta
Llama 4 Maverick
Input1,000,000 tokens
Output1,000,000 tokens
Tue Apr 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Llama 4 Maverick 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 Maverick

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek R1 Zero is licensed under MIT, while Llama 4 Maverick 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 Maverick

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 Maverick was released on 2025-04-05.

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

DeepSeek R1 Zero

Jan 20, 2025

1.2 years ago

Llama 4 Maverick

Apr 5, 2025

1.0 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
Higher GPQA score (73.3% vs 69.8%)
Higher LiveCodeBench score (50.0% vs 43.4%)
Meta
Larger context window (1,000,000 tokens)
Supports multimodal inputs

Detailed Comparison

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

FAQ

Common questions about DeepSeek R1 Zero vs Llama 4 Maverick

DeepSeek R1 Zero significantly outperforms across most benchmarks. DeepSeek R1 Zero is made by DeepSeek and Llama 4 Maverick is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%. Llama 4 Maverick scores DocVQA: 94.4%, MGSM: 92.3%, ChartQA: 90.0%, MMLU: 85.5%, MMLU-Pro: 80.5%.
DeepSeek R1 Zero supports an unknown number of tokens and Llama 4 Maverick supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
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.
DeepSeek R1 Zero is developed by DeepSeek and Llama 4 Maverick is developed by Meta.