Mistral Small 3.2 24B Instruct vs Muse Wonder
Muse Wonder leads the LLM Stats Score 47.9 to 8.4. Mistral Small 3.2 24B Instruct is 75.3x cheaper per token.
Mistral AI · Meta · Updated for 2026
Which is better?
Muse Wonder leads the overall LLM Stats Score 47.9 to 8.4, ranking #29 overall.
On price, Mistral Small 3.2 24B Instruct is roughly 75.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Wonder also accepts a larger context window (1,048,576 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 Mistral Small 3.2 24B Instruct
- cost matters — it's about 75.3x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Muse Wonder
- overall performance matters — it scores 47.9 and ranks #29 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for Mistral Small 3.2 24B Instruct · 16 for Muse Wonder
Mistral Small 3.2 24B Instruct and Muse Wonderdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Mistral Small 3.2 24B Instruct ($0.07/1M tokens) is 53.3x cheaper than Muse Wonder ($4.00/1M tokens).
For output processing, Mistral Small 3.2 24B Instruct ($0.20/1M tokens) is 100.0x cheaper than Muse Wonder ($20.00/1M tokens).
In conclusion, Muse Wonder is more expensive than Mistral Small 3.2 24B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Wonder accepts 1,048,576 input tokens compared to Mistral Small 3.2 24B Instruct's 128,000 tokens. Only Mistral Small 3.2 24B Instruct specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both Mistral Small 3.2 24B Instruct and Muse Wonder support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Mistral Small 3.2 24B Instruct
Muse Wonder
License
Usage and distribution terms
Mistral Small 3.2 24B Instruct is licensed under Apache 2.0, while Muse Wonder uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Mistral Small 3.2 24B Instruct was released on 2025-06-20, while Muse Wonder was released on 2026-10-12.
Muse Wonder is 16 months newer than Mistral Small 3.2 24B Instruct.
Jun 20, 2025
1.3 years ago
Oct 12, 2026
-1 days ago
1.3yr newerKnowledge Cutoff
When training data ends
Mistral Small 3.2 24B Instruct has a documented knowledge cutoff of 2023-10-01, while Muse Wonder's cutoff date is not specified.
We can confirm Mistral Small 3.2 24B Instruct's training data extends to 2023-10-01, but cannot make a direct comparison without Muse Wonder's cutoff date.
Oct 2023
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Provider Availability
Mistral Small 3.2 24B Instruct is available from DeepInfra. Muse Wonder is available from Meta Model API.
Mistral Small 3.2 24B Instruct
Muse Wonder
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Small 3.2 24B Instruct and Muse Wonder side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Small 3.2 24B Instruct vs Muse Wonder.