Llama 3.2 90B Instruct vs Mistral Small 3.1 24B Base
Llama 3.2 90B Instruct and Mistral Small 3.1 24B Base are closely matched at 5.2 and 0.3 on the LLM Stats Score. Mistral Small 3.1 24B Base is 2.4x cheaper per token.
Meta · Mistral AI · Updated for 2026
Which is better?
Llama 3.2 90B Instruct and Mistral Small 3.1 24B Base are closely matched on the overall LLM Stats Score at 5.2 and 0.3.
In the 3 individual benchmarks reported for both models, Llama 3.2 90B Instruct wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Mistral Small 3.1 24B Base is roughly 2.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Llama 3.2 90B Instruct
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
Choose Mistral Small 3.1 24B Base
- cost matters — it's about 2.4x cheaper per token
- you want the most recent training data — it shipped Mar 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Llama 3.2 90B Instruct · 5 for Mistral Small 3.1 24B Base
Llama 3.2 90B Instruct outperforms in 3 benchmarks (GPQA, MMLU, MMMU), while Mistral Small 3.1 24B Base is better at 0 benchmarks.
Llama 3.2 90B Instruct 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, Llama 3.2 90B Instruct ($0.35/1M tokens) is 3.5x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).
For output processing, Llama 3.2 90B Instruct ($0.40/1M tokens) is 1.3x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).
In conclusion, Llama 3.2 90B Instruct is more expensive than Mistral Small 3.1 24B Base.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 3.2 90B Instruct has 66.0B more parameters than Mistral Small 3.1 24B Base, making it 275.0% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Llama 3.2 90B Instruct and Mistral Small 3.1 24B Base support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Llama 3.2 90B Instruct
Mistral Small 3.1 24B Base
License
Usage and distribution terms
Llama 3.2 90B Instruct is licensed under Llama 3.2, while Mistral Small 3.1 24B Base uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.2
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Llama 3.2 90B Instruct was released on 2024-09-25, while Mistral Small 3.1 24B Base was released on 2025-03-17.
Mistral Small 3.1 24B Base is 6 months newer than Llama 3.2 90B Instruct.
Sep 25, 2024
2.0 years ago
Mar 17, 2025
1.6 years ago
5mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic. Mistral Small 3.1 24B Base is available from Mistral AI.
Llama 3.2 90B Instruct
Mistral Small 3.1 24B Base
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.2 90B Instruct and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.2 90B Instruct vs Mistral Small 3.1 24B Base.