Model Comparison

DeepSeek VL2 Tiny vs Llama 3.2 90B InstructWhich is better in 2026?

Llama 3.2 90B Instruct significantly outperforms across most benchmarks.

Verdict: DeepSeek VL2 Tiny vs Llama 3.2 90B Instruct — which is better?

DeepSeek VL2 Tiny (by DeepSeek) and Llama 3.2 90B Instruct (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 VL2 Tiny outperforms in 1 benchmarks (TextVQA), while Llama 3.2 90B Instruct is better at 5 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMMU). Llama 3.2 90B Instruct significantly outperforms across most benchmarks.

Choose DeepSeek VL2 Tiny if…

  • you want the most recent training data — it shipped Dec 2024

Choose Llama 3.2 90B Instruct if…

  • you want the strongest raw capability — it leads on 5 of 6 shared benchmarks
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

DeepSeek VL2 Tiny outperforms in 1 benchmarks (TextVQA), while Llama 3.2 90B Instruct is better at 5 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMMU).

Llama 3.2 90B Instruct significantly outperforms across most benchmarks.

Thu Jun 11 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

87.0B diff

Llama 3.2 90B Instruct has 87.0B more parameters than DeepSeek VL2 Tiny, making it 2900.0% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Meta
Llama 3.2 90B Instruct
90.0Bparameters
3.0B
DeepSeek VL2 Tiny
90.0B
Llama 3.2 90B Instruct

Context Window

Maximum input and output token capacity

Only Llama 3.2 90B Instruct specifies input context (128,000 tokens). Only Llama 3.2 90B Instruct specifies output context (128,000 tokens).

DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Thu Jun 11 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Tiny and Llama 3.2 90B Instruct 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 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while Llama 3.2 90B Instruct uses Llama 3.2.

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

DeepSeek VL2 Tiny

deepseek

Open weights

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while Llama 3.2 90B Instruct was released on 2024-09-25.

DeepSeek VL2 Tiny is 3 months newer than Llama 3.2 90B Instruct.

DeepSeek VL2 Tiny

Dec 13, 2024

1.5 years ago

2mo newer
Llama 3.2 90B Instruct

Sep 25, 2024

1.7 years ago

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 TextVQA score (80.7% vs 73.5%)
Meta
Larger context window (128,000 tokens)
Higher AI2D score (92.3% vs 71.6%)
Higher ChartQA score (85.5% vs 81.0%)
Higher DocVQA score (90.1% vs 88.9%)
Higher MathVista score (57.3% vs 53.6%)
Higher MMMU score (60.3% vs 40.7%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
Meta
Llama 3.2 90B Instruct

FAQ

Common questions about DeepSeek VL2 Tiny vs Llama 3.2 90B Instruct.

Which is better, DeepSeek VL2 Tiny or Llama 3.2 90B Instruct?

Llama 3.2 90B Instruct significantly outperforms across most benchmarks. DeepSeek VL2 Tiny is made by DeepSeek and Llama 3.2 90B Instruct 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 3.2 90B Instruct in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.

What are the context window sizes for DeepSeek VL2 Tiny and Llama 3.2 90B Instruct?

DeepSeek VL2 Tiny supports an unknown number of tokens and Llama 3.2 90B Instruct supports 128K 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 3.2 90B Instruct?

Key differences include licensing (deepseek vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 Tiny and Llama 3.2 90B Instruct?

DeepSeek VL2 Tiny is developed by DeepSeek and Llama 3.2 90B Instruct is developed by Meta.

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