Model Comparison

DeepSeek-V2.5 vs Llama 4 Maverick

Both models are evenly matched across the benchmarks. DeepSeek-V2.5 is 1.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V2.5 outperforms in 1 benchmarks (MATH), while Llama 4 Maverick is better at 1 benchmark (MMLU).

Both models are evenly matched across the benchmarks.

Fri May 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V2.5 costs less

For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 1.2x cheaper than Llama 4 Maverick ($0.17/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 2.1x cheaper than Llama 4 Maverick ($0.60/1M tokens).

In conclusion, Llama 4 Maverick is more expensive than DeepSeek-V2.5.*

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

Lowest available price from all providers
Fri May 01 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
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

164.0B diff

Llama 4 Maverick has 164.0B more parameters than DeepSeek-V2.5, making it 69.5% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Meta
Llama 4 Maverick
400.0Bparameters
236.0B
DeepSeek-V2.5
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-V2.5's 8,192 tokens. Llama 4 Maverick can generate longer responses up to 1,000,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Meta
Llama 4 Maverick
Input1,000,000 tokens
Output1,000,000 tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 4 Maverick supports multimodal inputs, whereas DeepSeek-V2.5 does not.

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

DeepSeek-V2.5

Text
Images
Audio
Video

Llama 4 Maverick

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, 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-V2.5

deepseek

Open weights

Llama 4 Maverick

Llama 4 Community License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while Llama 4 Maverick was released on 2025-04-05.

Llama 4 Maverick is 11 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.0 years ago

Llama 4 Maverick

Apr 5, 2025

1.1 years ago

11mo 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-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Llama 4 Maverick is available from DeepInfra, Novita, Lambda, Groq, Fireworks, Together, Sambanova.

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

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
Less expensive input tokens
Less expensive output tokens
Higher MATH score (74.7% vs 61.2%)
Meta
Larger context window (1,000,000 tokens)
Supports multimodal inputs
Higher MMLU score (85.5% vs 80.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Meta
Llama 4 Maverick

FAQ

Common questions about DeepSeek-V2.5 vs Llama 4 Maverick

Both models are evenly matched across the benchmarks. DeepSeek-V2.5 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-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. Llama 4 Maverick scores DocVQA: 94.4%, MGSM: 92.3%, ChartQA: 90.0%, MMLU: 85.5%, MMLU-Pro: 80.5%.
DeepSeek-V2.5 is 1.2x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. Llama 4 Maverick costs $0.17/M input and $0.60/M output via deepinfra.
DeepSeek-V2.5 supports 8K 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 context window (8K vs 1.0M), input pricing ($0.14 vs $0.17/M), multimodal support (no vs yes), licensing (deepseek vs Llama 4 Community License Agreement). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and Llama 4 Maverick is developed by Meta.