IBM Granite 4.2 8B vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 46.2 to 19.6. IBM Granite 4.2 8B is 9.6x cheaper per token.
IBM · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 46.2 to 19.6, ranking #34 overall.
In the 1 individual benchmarks reported for both models, Mistral Large 4 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, IBM Granite 4.2 8B is roughly 9.6x 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 IBM Granite 4.2 8B
- cost matters — it's about 9.6x 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 and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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
18 reported for IBM Granite 4.2 8B · 18 for Mistral Large 4
IBM Granite 4.2 8B outperforms in 0 benchmarks, while Mistral Large 4 is better at 1 benchmark (SciCode).
Mistral Large 4 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, IBM Granite 4.2 8B ($0.06/1M tokens) is 11.3x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, IBM Granite 4.2 8B ($0.25/1M tokens) is 8.4x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than IBM Granite 4.2 8B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 1042.0B more parameters than IBM Granite 4.2 8B, making it 13025.0% larger.
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to IBM Granite 4.2 8B's 131,072 tokens. Only IBM Granite 4.2 8B specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Large 4 supports multimodal inputs, whereas IBM Granite 4.2 8B does not.
Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
IBM Granite 4.2 8B
Mistral Large 4
License
Usage and distribution terms
IBM Granite 4.2 8B is licensed under Apache 2.0, while Mistral Large 4 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
IBM Granite 4.2 8B was released on 2026-08-25, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 1 month newer than IBM Granite 4.2 8B.
Aug 25, 2026
1 months ago
Oct 6, 2026
2 days ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
IBM Granite 4.2 8B is available from DeepInfra. Mistral Large 4 is available from Mistral AI.
IBM Granite 4.2 8B
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against IBM Granite 4.2 8B and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about IBM Granite 4.2 8B vs Mistral Large 4.