Model Comparison
Gemini 1.0 Pro vs Pixtral-12BWhich is better in 2026?
Pixtral-12B shows notably better performance in the majority of benchmarks. Pixtral-12B is 5.0x cheaper per token.
Verdict: Gemini 1.0 Pro vs Pixtral-12B — which is better?
Gemini 1.0 Pro (by Google) and Pixtral-12B (by Mistral AI) 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.
Gemini 1.0 Pro outperforms in 1 benchmarks (MMLU), while Pixtral-12B is better at 3 benchmarks (MATH, MathVista, MMMU). Pixtral-12B shows notably better performance in the majority of benchmarks.
On price, Pixtral-12B is roughly 5.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Pixtral-12B also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 1.0 Pro if…
- you want predictable pricing at $0.50/M input and $1.50/M output
Choose Pixtral-12B if…
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
- cost matters — it's about 5.0x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Sep 2024
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 1.0 Pro outperforms in 1 benchmarks (MMLU), while Pixtral-12B is better at 3 benchmarks (MATH, MathVista, MMMU).
Pixtral-12B shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.0 Pro ($0.50/1M tokens) is 3.3x more expensive than Pixtral-12B ($0.15/1M tokens).
For output processing, Gemini 1.0 Pro ($1.50/1M tokens) is 10.0x more expensive than Pixtral-12B ($0.15/1M tokens).
In conclusion, Gemini 1.0 Pro is more expensive than Pixtral-12B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Pixtral-12B accepts 128,000 input tokens compared to Gemini 1.0 Pro's 32,760 tokens. Both models can generate responses up to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Pixtral-12B supports multimodal inputs, whereas Gemini 1.0 Pro does not.
Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 1.0 Pro
Pixtral-12B
License
Usage and distribution terms
Gemini 1.0 Pro 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.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemini 1.0 Pro was released on 2024-02-15, while Pixtral-12B was released on 2024-09-17.
Pixtral-12B is 7 months newer than Gemini 1.0 Pro.
Feb 15, 2024
2.3 years ago
Sep 17, 2024
1.7 years ago
7mo newerKnowledge Cutoff
When training data ends
Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while Pixtral-12B's cutoff date is not specified.
We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without Pixtral-12B's cutoff date.
Feb 2024
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Provider Availability
Gemini 1.0 Pro is available from Google. Pixtral-12B is available from Mistral AI.
Gemini 1.0 Pro
Pixtral-12B
Outputs Comparison
Key Takeaways
Pixtral-12B
View detailsMistral AI
Detailed Comparison
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FAQ
Common questions about Gemini 1.0 Pro vs Pixtral-12B.