Model Comparison

DeepSeek-V3.1 vs Llama 4 Maverick

DeepSeek-V3.1 significantly outperforms across most benchmarks. Llama 4 Maverick is 1.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3.1 outperforms in 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro), while Llama 4 Maverick is better at 0 benchmarks.

DeepSeek-V3.1 significantly outperforms across most benchmarks.

Wed May 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 4 Maverick costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 1.6x more expensive than Llama 4 Maverick ($0.17/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 1.7x more expensive than Llama 4 Maverick ($0.60/1M tokens).

In conclusion, DeepSeek-V3.1 is more expensive than Llama 4 Maverick.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed May 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
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-V3.1 has 271.0B more parameters than Llama 4 Maverick, making it 67.8% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Meta
Llama 4 Maverick
400.0Bparameters
671.0B
DeepSeek-V3.1
400.0B
Llama 4 Maverick

Context Window

Maximum input and output token capacity

Llama 4 Maverick accepts 1,000,000 input tokens compared to DeepSeek-V3.1's 163,840 tokens. Llama 4 Maverick can generate longer responses up to 1,000,000 tokens, while DeepSeek-V3.1 is limited to 163,840 tokens.

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Meta
Llama 4 Maverick
Input1,000,000 tokens
Output1,000,000 tokens
Wed May 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 4 Maverick supports multimodal inputs, whereas DeepSeek-V3.1 does not.

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

DeepSeek-V3.1

Text
Images
Audio
Video

Llama 4 Maverick

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 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-V3.1

MIT

Open weights

Llama 4 Maverick

Llama 4 Community License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Llama 4 Maverick was released on 2025-04-05.

Llama 4 Maverick is 3 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.3 years ago

Llama 4 Maverick

Apr 5, 2025

1.1 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

Provider Availability

DeepSeek-V3.1 is available from DeepInfra, Novita. Llama 4 Maverick is available from DeepInfra, Novita, Lambda, Groq, Fireworks, Together, Sambanova.

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

Llama 4 Maverick

deepinfra logo
Deepinfra
Input Price:Input: $0.17/1MOutput Price:Output: $0.60/1M
novita logo
Novita
Input Price:Input: $0.17/1MOutput Price:Output: $0.85/1M
lambda logo
Lambda
Input Price:Input: $0.18/1MOutput Price:Output: $0.60/1M
groq logo
Groq
Input Price:Input: $0.20/1MOutput Price:Output: $0.60/1M
fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.88/1M
together logo
Together
Input Price:Input: $0.27/1MOutput Price:Output: $0.85/1M
sambanova logo
Sambanova
Input Price:Input: $0.63/1MOutput Price:Output: $1.79/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Higher GPQA score (74.9% vs 69.8%)
Higher LiveCodeBench score (56.4% vs 43.4%)
Higher MMLU-Pro score (83.7% vs 80.5%)
Meta
Larger context window (1,000,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Meta
Llama 4 Maverick

FAQ

Common questions about DeepSeek-V3.1 vs Llama 4 Maverick.

Which is better, DeepSeek-V3.1 or Llama 4 Maverick?

DeepSeek-V3.1 significantly outperforms across most benchmarks. DeepSeek-V3.1 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.

How does DeepSeek-V3.1 compare to Llama 4 Maverick in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Llama 4 Maverick scores DocVQA: 94.4%, MGSM: 92.3%, ChartQA: 90.0%, MMLU: 85.5%, MMLU-Pro: 80.5%.

Is DeepSeek-V3.1 cheaper than Llama 4 Maverick?

Llama 4 Maverick is 1.6x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. Llama 4 Maverick costs $0.17/M input and $0.60/M output via deepinfra.

What are the context window sizes for DeepSeek-V3.1 and Llama 4 Maverick?

DeepSeek-V3.1 supports 164K 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.

What are the main differences between DeepSeek-V3.1 and Llama 4 Maverick?

Key differences include context window (164K vs 1.0M), input pricing ($0.27 vs $0.17/M), 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-V3.1 and Llama 4 Maverick?

DeepSeek-V3.1 is developed by DeepSeek and Llama 4 Maverick is developed by Meta.