Llama 3.2 11B Instruct vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 46.2 to -1.3. Llama 3.2 11B Instruct is 20.6x cheaper per token.
Meta · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 46.2 to -1.3, ranking #34 overall.
On price, Llama 3.2 11B Instruct is roughly 20.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Large 4 also accepts a larger context window (1,000,000 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 Llama 3.2 11B Instruct
- cost matters — it's about 20.6x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Mistral Large 4
- overall performance matters — it scores 46.2 and ranks #34 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,000,000 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
11 reported for Llama 3.2 11B Instruct · 18 for Mistral Large 4
Llama 3.2 11B Instruct and Mistral Large 4don'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, Llama 3.2 11B Instruct ($0.05/1M tokens) is 13.6x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, Llama 3.2 11B Instruct ($0.05/1M tokens) is 41.8x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than Llama 3.2 11B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 1039.4B more parameters than Llama 3.2 11B Instruct, making it 9805.7% larger.
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to Llama 3.2 11B Instruct's 128,000 tokens. Only Llama 3.2 11B Instruct specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both Llama 3.2 11B Instruct and Mistral Large 4 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Llama 3.2 11B Instruct
Mistral Large 4
License
Usage and distribution terms
Llama 3.2 11B Instruct is licensed under Llama 3.2 Community License, while Mistral Large 4 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Llama 3.2 Community License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Llama 3.2 11B Instruct was released on 2024-09-25, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 25 months newer than Llama 3.2 11B Instruct.
Sep 25, 2024
2.0 years ago
Oct 6, 2026
2 days ago
2.0yr newerKnowledge Cutoff
When training data ends
Llama 3.2 11B Instruct has a documented knowledge cutoff of 2023-12-31, while Mistral Large 4's cutoff date is not specified.
We can confirm Llama 3.2 11B Instruct's training data extends to 2023-12-31, but cannot make a direct comparison without Mistral Large 4's cutoff date.
Dec 2023
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Provider Availability
Llama 3.2 11B Instruct is available from DeepInfra, Sambanova, Bedrock, Groq, Together, Fireworks. Mistral Large 4 is available from Mistral AI.
Llama 3.2 11B Instruct
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Llama 3.2 11B Instruct and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Llama 3.2 11B Instruct vs Mistral Large 4.