Grok-1.5 vs Pixtral-12B Comparison

Comparing Grok-1.5 and Pixtral-12B across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Grok-1.5 outperforms in 4 benchmarks (HumanEval, MATH, MMLU, MMMU), while Pixtral-12B is better at 2 benchmarks (DocVQA, MathVista).

Grok-1.5 shows notably better performance in the majority of benchmarks.

Thu Mar 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Mar 19 2026 • llm-stats.com
xAI
Grok-1.5
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Mistral AI
Pixtral-12B
Input tokens$0.15
Output tokens$0.15
Best providerMistral
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Context Window

Maximum input and output token capacity

Only Pixtral-12B specifies input context (128,000 tokens). Only Pixtral-12B specifies output context (8,192 tokens).

xAI
Grok-1.5
Input- tokens
Output- tokens
Mistral AI
Pixtral-12B
Input128,000 tokens
Output8,192 tokens
Thu Mar 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Pixtral-12B supports multimodal inputs, whereas Grok-1.5 does not.

Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Grok-1.5

Text
Images
Audio
Video

Pixtral-12B

Text
Images
Audio
Video

License

Usage and distribution terms

Grok-1.5 is licensed under a proprietary license, while Pixtral-12B uses Apache 2.0.

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

Grok-1.5

Proprietary

Closed source

Pixtral-12B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Grok-1.5 was released on 2024-03-28, while Pixtral-12B was released on 2024-09-17.

Pixtral-12B is 6 months newer than Grok-1.5.

Grok-1.5

Mar 28, 2024

2.0 years ago

Pixtral-12B

Sep 17, 2024

1.5 years ago

5mo 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

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Key Takeaways

Higher HumanEval score (74.1% vs 72.0%)
Higher MATH score (50.6% vs 48.1%)
Higher MMLU score (81.3% vs 69.2%)
Higher MMMU score (53.6% vs 52.5%)
Larger context window (128,000 tokens)
Supports multimodal inputs
Has open weights
Higher DocVQA score (90.7% vs 85.6%)
Higher MathVista score (58.0% vs 52.8%)

Detailed Comparison

AI Model Comparison Table
Feature
xAI
Grok-1.5
Mistral AI
Pixtral-12B