GPT-3.5 Turbo vs Pixtral-12B
Pixtral-12B leads the LLM Stats Score -1.4 to -9.2. Pixtral-12B is 5.0x cheaper per token.
OpenAI · Mistral AI · Updated for 2026
Which is better?
Pixtral-12B leads the overall LLM Stats Score -1.4 to -9.2, ranking #322 overall.
In the 5 individual benchmarks reported for both models, Pixtral-12B wins 4; 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 GPT-3.5 Turbo
- you want predictable pricing at $0.50/M input and $1.50/M output
Choose Pixtral-12B
- overall performance matters — it scores -1.4 and ranks #322 on LLM Stats
- you value its reported benchmark strengths — it wins 4 of 5 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
8 reported for GPT-3.5 Turbo · 12 for Pixtral-12B
GPT-3.5 Turbo outperforms in 1 benchmarks (MMLU), while Pixtral-12B is better at 4 benchmarks (HumanEval, MATH, MathVista, MMMU).
Pixtral-12B significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-3.5 Turbo ($0.50/1M tokens) is 3.3x more expensive than Pixtral-12B ($0.15/1M tokens).
For output processing, GPT-3.5 Turbo ($1.50/1M tokens) is 10.0x more expensive than Pixtral-12B ($0.15/1M tokens).
In conclusion, GPT-3.5 Turbo 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 GPT-3.5 Turbo's 16,385 tokens. Pixtral-12B can generate longer responses up to 8,192 tokens, while GPT-3.5 Turbo is limited to 4,096 tokens.
Input capabilities
Documented input modalities across available providers
Pixtral-12B supports multimodal inputs, whereas GPT-3.5 Turbo does not.
Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-3.5 Turbo
Pixtral-12B
License
Usage and distribution terms
GPT-3.5 Turbo 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
GPT-3.5 Turbo was released on 2023-03-21, while Pixtral-12B was released on 2024-09-17.
Pixtral-12B is 18 months newer than GPT-3.5 Turbo.
Mar 21, 2023
3.5 years ago
Sep 17, 2024
2.0 years ago
1.5yr newerKnowledge Cutoff
When training data ends
GPT-3.5 Turbo has a documented knowledge cutoff of 2021-09-30, while Pixtral-12B's cutoff date is not specified.
We can confirm GPT-3.5 Turbo's training data extends to 2021-09-30, but cannot make a direct comparison without Pixtral-12B's cutoff date.
Sep 2021
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Provider Availability
GPT-3.5 Turbo is available from Azure, OpenAI. Pixtral-12B is available from Mistral AI.
GPT-3.5 Turbo
Pixtral-12B
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-3.5 Turbo and Pixtral-12B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-3.5 Turbo vs Pixtral-12B.