Gemini 1.0 Pro vs Pixtral-12B
Gemini 1.0 Pro and Pixtral-12B are closely matched at -5.4 and -1.6 on the LLM Stats Score. Pixtral-12B is 5.0x cheaper per token.
Google · Mistral AI · Updated for 2026
Which is better?
Gemini 1.0 Pro and Pixtral-12B are closely matched on the overall LLM Stats Score at -5.4 and -1.6.
In the 4 individual benchmarks reported for both models, Pixtral-12B wins 3; this is a narrower head-to-head signal than the composite indexes.
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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 1.0 Pro
- you want predictable pricing at $0.50/M input and $1.50/M output
Choose Pixtral-12B
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
- 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
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for Gemini 1.0 Pro · 12 for Pixtral-12B
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.
Human preference
Blind head-to-head votes and playground preference scores
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
Documented input modalities across available providers
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
2.6 years ago
Sep 17, 2024
2.1 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
Judge for yourself.
Run your own prompts against Gemini 1.0 Pro and Pixtral-12B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.0 Pro vs Pixtral-12B.