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Llama 3.2 90B Instruct vs Mistral Small 3.2 24B Instruct

Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct are closely matched at 5.2 and 8.4 on the LLM Stats Score. Mistral Small 3.2 24B Instruct is 3.4x cheaper per token.

Meta · Mistral AI · Updated for 2026

Which is better?

Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct are closely matched on the overall LLM Stats Score at 5.2 and 8.4.

In the 8 individual benchmarks reported for both models, Mistral Small 3.2 24B Instruct wins 6; this is a narrower head-to-head signal than the composite indexes.

On price, Mistral Small 3.2 24B Instruct is roughly 3.4x 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 want predictable pricing at $0.35/M input and $0.40/M output

Choose Mistral Small 3.2 24B Instruct

  • you value its reported benchmark strengths — it wins 6 of 8 exact shared results
  • cost matters — it's about 3.4x cheaper per token
  • you want the most recent training data — it shipped Jun 2025

At a glance

The differences that matter most.

Core performance indexes
5.2
#313
8.4
#294
6.7
#301
7.9
#295
Cost, coverage & limits
Benchmark wins
2 of 8
6 of 8
Input price
$0.35 / M
$0.07 / M
Output price
$0.40 / M
$0.20 / M
Context window
128,000
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Llama 3.2 90B Instruct
Mistral Small 3.2 24B Instruct
11.6#244
11.1#251
2.8#175
10.1#132
5.5#147
13.1#112
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

13 reported for Llama 3.2 90B Instruct · 15 for Mistral Small 3.2 24B Instruct

8 shared

Llama 3.2 90B Instruct outperforms in 2 benchmarks (GPQA, MMLU), while Mistral Small 3.2 24B Instruct is better at 6 benchmarks (AI2D, ChartQA, DocVQA, MATH, MathVista, MMMU).

Mistral Small 3.2 24B Instruct shows notably better performance in the majority of benchmarks.

Thu Oct 08 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Mistral Small 3.2 24B Instruct costs less

For input processing, Llama 3.2 90B Instruct ($0.35/1M tokens) is 4.7x more expensive than Mistral Small 3.2 24B Instruct ($0.07/1M tokens).

For output processing, Llama 3.2 90B Instruct ($0.40/1M tokens) is 2.0x more expensive than Mistral Small 3.2 24B Instruct ($0.20/1M tokens).

In conclusion, Llama 3.2 90B Instruct is more expensive than Mistral Small 3.2 24B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Oct 08 2026 • llm-stats.com
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Mistral AI
Mistral Small 3.2 24B Instruct
Input tokens$0.07
Output tokens$0.20
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

66.4B diff

Llama 3.2 90B Instruct has 66.4B more parameters than Mistral Small 3.2 24B Instruct, making it 281.4% larger.

Meta
Llama 3.2 90B Instruct
90.0Bparameters
Mistral AI
Mistral Small 3.2 24B Instruct
23.6Bparameters
90.0B
Llama 3.2 90B Instruct
23.6B
Mistral Small 3.2 24B Instruct

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.

Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Mistral AI
Mistral Small 3.2 24B Instruct
Input128,000 tokens
Output128,000 tokens
Thu Oct 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Llama 3.2 90B Instruct

Text
Images
Audio
Video

Mistral Small 3.2 24B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.2 90B Instruct is licensed under Llama 3.2, while Mistral Small 3.2 24B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Mistral Small 3.2 24B Instruct

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 3.2 24B Instruct was released on 2025-06-20.

Mistral Small 3.2 24B Instruct is 9 months newer than Llama 3.2 90B Instruct.

Llama 3.2 90B Instruct

Sep 25, 2024

2.0 years ago

Mistral Small 3.2 24B Instruct

Jun 20, 2025

1.3 years ago

8mo newer

Knowledge Cutoff

When training data ends

Mistral Small 3.2 24B Instruct has a documented knowledge cutoff of 2023-10-01, while Llama 3.2 90B Instruct'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 Llama 3.2 90B Instruct's cutoff date.

Llama 3.2 90B Instruct

—

Mistral Small 3.2 24B Instruct

Oct 2023

Provider Availability

Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic. Mistral Small 3.2 24B Instruct is available from DeepInfra.

Llama 3.2 90B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

Mistral Small 3.2 24B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.07/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct side-by-side, then vote on the output you prefer.

Llama 3.2 90B Instruct
✓ Preferred
Mistral Small 3.2 24B Instruct
Open in Playground

FAQ

Common questions about Llama 3.2 90B Instruct vs Mistral Small 3.2 24B Instruct.

Which is better, Llama 3.2 90B Instruct or Mistral Small 3.2 24B Instruct?

Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct are closely matched on the LLM Stats Score at 5.2 and 8.4. Llama 3.2 90B Instruct is made by Meta and Mistral Small 3.2 24B Instruct is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Llama 3.2 90B Instruct compare to Mistral Small 3.2 24B Instruct in benchmarks?

Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%. Mistral Small 3.2 24B Instruct scores DocVQA: 94.9%, AI2D: 92.9%, HumanEval Plus: 92.9%, ChartQA: 87.4%, IF: 84.8%.

Is Llama 3.2 90B Instruct cheaper than Mistral Small 3.2 24B Instruct?

Mistral Small 3.2 24B Instruct is 4.7x cheaper for input tokens. Llama 3.2 90B Instruct costs $0.35/M input and $0.40/M output via deepinfra. Mistral Small 3.2 24B Instruct costs $0.07/M input and $0.20/M output via deepinfra.

What are the context window sizes for Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct?

Llama 3.2 90B Instruct supports 128K tokens and Mistral Small 3.2 24B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct?

Key differences include LLM Stats Score (5.2 vs 8.4), input pricing ($0.35 vs $0.07/M), licensing (Llama 3.2 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.2 90B Instruct and Mistral Small 3.2 24B Instruct?

Llama 3.2 90B Instruct is developed by Meta and Mistral Small 3.2 24B Instruct is developed by Mistral AI.