Model Comparison

Llama 4 Scout vs Pixtral Large

Llama 4 Scout significantly outperforms across most benchmarks. Llama 4 Scout is 22.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Llama 4 Scout outperforms in 4 benchmarks (ChartQA, DocVQA, MathVista, MMMU), while Pixtral Large is better at 0 benchmarks.

Llama 4 Scout significantly outperforms across most benchmarks.

Thu May 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 4 Scout costs less

For input processing, Llama 4 Scout ($0.08/1M tokens) is 25.0x cheaper than Pixtral Large ($2.00/1M tokens).

For output processing, Llama 4 Scout ($0.30/1M tokens) is 20.0x cheaper than Pixtral Large ($6.00/1M tokens).

In conclusion, Pixtral Large is more expensive than Llama 4 Scout.*

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

Lowest available price from all providers
Thu May 21 2026 • llm-stats.com
Meta
Llama 4 Scout
Input tokens$0.08
Output tokens$0.30
Best providerDeepinfra
Mistral AI
Pixtral Large
Input tokens$2.00
Output tokens$6.00
Best providerMistral
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Model Size

Parameter count comparison

15.0B diff

Pixtral Large has 15.0B more parameters than Llama 4 Scout, making it 13.8% larger.

Meta
Llama 4 Scout
109.0Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
109.0B
Llama 4 Scout
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

Llama 4 Scout accepts 10,000,000 input tokens compared to Pixtral Large's 128,000 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Pixtral Large is limited to 128,000 tokens.

Meta
Llama 4 Scout
Input10,000,000 tokens
Output10,000,000 tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Thu May 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Llama 4 Scout and Pixtral Large support multimodal inputs.

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

Llama 4 Scout

Text
Images
Audio
Video

Pixtral Large

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 4 Scout is licensed under Llama 4 Community License Agreement, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.

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

Llama 4 Scout

Llama 4 Community License Agreement

Open weights

Pixtral Large

Mistral Research License (MRL) for research; Mistral Commercial License for commercial use

Open weights

Release Timeline

When each model was launched

Llama 4 Scout was released on 2025-04-05, while Pixtral Large was released on 2024-11-18.

Llama 4 Scout is 5 months newer than Pixtral Large.

Llama 4 Scout

Apr 5, 2025

1.1 years ago

4mo newer
Pixtral Large

Nov 18, 2024

1.5 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

Provider Availability

Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. Pixtral Large is available from Mistral AI.

Llama 4 Scout

deepinfra logo
Deepinfra
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
lambda logo
Lambda
Input Price:Input: $0.08/1MOutput Price:Output: $0.30/1M
novita logo
Novita
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
groq logo
Groq
Input Price:Input: $0.11/1MOutput Price:Output: $0.34/1M
fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
together logo
Together
Input Price:Input: $0.18/1MOutput Price:Output: $0.59/1M

Pixtral Large

mistral logo
Mistral
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Meta
Larger context window (10,000,000 tokens)
Less expensive input tokens
Less expensive output tokens
Higher ChartQA score (88.8% vs 88.1%)
Higher DocVQA score (94.4% vs 93.3%)
Higher MathVista score (70.7% vs 69.4%)
Higher MMMU score (69.4% vs 64.0%)
Mistral AI

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

Detailed Comparison

AI Model Comparison Table
Feature
Meta
Llama 4 Scout
Mistral AI
Pixtral Large

FAQ

Common questions about Llama 4 Scout vs Pixtral Large.

Which is better, Llama 4 Scout or Pixtral Large?

Llama 4 Scout significantly outperforms across most benchmarks. Llama 4 Scout is made by Meta and Pixtral Large is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Llama 4 Scout compare to Pixtral Large in benchmarks?

Llama 4 Scout scores DocVQA: 94.4%, MGSM: 90.6%, ChartQA: 88.8%, MMLU: 79.6%, MMLU-Pro: 74.3%. Pixtral Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.

Is Llama 4 Scout cheaper than Pixtral Large?

Llama 4 Scout is 25.0x cheaper for input tokens. Llama 4 Scout costs $0.08/M input and $0.30/M output via deepinfra. Pixtral Large costs $2.00/M input and $6.00/M output via mistral.

What are the context window sizes for Llama 4 Scout and Pixtral Large?

Llama 4 Scout supports 10.0M tokens and Pixtral Large 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 Llama 4 Scout and Pixtral Large?

Key differences include context window (10.0M vs 128K), input pricing ($0.08 vs $2.00/M), licensing (Llama 4 Community License Agreement vs Mistral Research License (MRL) for research; Mistral Commercial License for commercial use). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 4 Scout and Pixtral Large?

Llama 4 Scout is developed by Meta and Pixtral Large is developed by Mistral AI.