Model Comparison

DeepSeek VL2 Tiny vs Llama 4 Maverick

Llama 4 Maverick significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek VL2 Tiny outperforms in 0 benchmarks, while Llama 4 Maverick is better at 4 benchmarks (ChartQA, DocVQA, MathVista, MMMU).

Llama 4 Maverick significantly outperforms across most benchmarks.

Sat May 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

397.0B diff

Llama 4 Maverick has 397.0B more parameters than DeepSeek VL2 Tiny, making it 13233.3% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Meta
Llama 4 Maverick
400.0Bparameters
3.0B
DeepSeek VL2 Tiny
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 VL2 Tiny
Input- tokens
Output- tokens
Meta
Llama 4 Maverick
Input1,000,000 tokens
Output1,000,000 tokens
Sat May 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Tiny and Llama 4 Maverick support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2 Tiny

Text
Images
Audio
Video

Llama 4 Maverick

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny 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 VL2 Tiny

deepseek

Open weights

Llama 4 Maverick

Llama 4 Community License Agreement

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while Llama 4 Maverick was released on 2025-04-05.

Llama 4 Maverick is 4 months newer than DeepSeek VL2 Tiny.

DeepSeek VL2 Tiny

Dec 13, 2024

1.5 years ago

Llama 4 Maverick

Apr 5, 2025

1.2 years ago

3mo 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

No standout differentiators in the data we have for this pair.

Meta
Larger context window (1,000,000 tokens)
Higher ChartQA score (90.0% vs 81.0%)
Higher DocVQA score (94.4% vs 88.9%)
Higher MathVista score (73.7% vs 53.6%)
Higher MMMU score (73.4% vs 40.7%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
Meta
Llama 4 Maverick

FAQ

Common questions about DeepSeek VL2 Tiny vs Llama 4 Maverick.

Which is better, DeepSeek VL2 Tiny or Llama 4 Maverick?

Llama 4 Maverick significantly outperforms across most benchmarks. DeepSeek VL2 Tiny 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 VL2 Tiny compare to Llama 4 Maverick in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. Llama 4 Maverick scores DocVQA: 94.4%, MGSM: 92.3%, ChartQA: 90.0%, MMLU: 85.5%, MMLU-Pro: 80.5%.

What are the context window sizes for DeepSeek VL2 Tiny and Llama 4 Maverick?

DeepSeek VL2 Tiny 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.

What are the main differences between DeepSeek VL2 Tiny and Llama 4 Maverick?

Key differences include licensing (deepseek vs Llama 4 Community License Agreement). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 Tiny and Llama 4 Maverick?

DeepSeek VL2 Tiny is developed by DeepSeek and Llama 4 Maverick is developed by Meta.