IBM Granite 4.2 30B vs Mistral Small 4
IBM Granite 4.2 30B and Mistral Small 4 are closely matched at 23.8 and 19.0 on the LLM Stats Score. Mistral Small 4 is 1.1x cheaper per token.
IBM · Mistral AI · Updated for 2026
Which is better?
IBM Granite 4.2 30B and Mistral Small 4 are closely matched on the overall LLM Stats Score at 23.8 and 19.0.
The models split the 4 individual benchmarks reported for both models evenly.
On price, Mistral Small 4 is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Small 4 also accepts a larger context window (256,000 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 30B
- you want the most recent training data — it shipped Aug 2026
Choose Mistral Small 4
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 256,000 token context window
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 30B · 9 for Mistral Small 4
IBM Granite 4.2 30B outperforms in 2 benchmarks (AIME 2025, IFBench), while Mistral Small 4 is better at 2 benchmarks (GPQA, MMLU-Pro).
Both models are evenly matched across the 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 30B ($0.16/1M tokens) is 1.1x more expensive than Mistral Small 4 ($0.15/1M tokens).
For output processing, IBM Granite 4.2 30B ($0.65/1M tokens) is 1.1x more expensive than Mistral Small 4 ($0.60/1M tokens).
In conclusion, IBM Granite 4.2 30B is more expensive than Mistral Small 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Small 4 has 89.0B more parameters than IBM Granite 4.2 30B, making it 296.7% larger.
Context Window
Maximum input and output token capacity
Mistral Small 4 accepts 256,000 input tokens compared to IBM Granite 4.2 30B's 131,072 tokens. Mistral Small 4 can generate longer responses up to 256,000 tokens, while IBM Granite 4.2 30B is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Mistral Small 4 supports multimodal inputs, whereas IBM Granite 4.2 30B does not.
Mistral Small 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
IBM Granite 4.2 30B
Mistral Small 4
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
IBM Granite 4.2 30B was released on 2026-08-25, while Mistral Small 4 was released on 2026-03-16.
IBM Granite 4.2 30B is 5 months newer than Mistral Small 4.
Aug 25, 2026
4 weeks ago
5mo newerMar 16, 2026
6 months ago
Knowledge 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 30B is available from DeepInfra. Mistral Small 4 is available from Mistral AI.
IBM Granite 4.2 30B
Mistral Small 4
Outputs Comparison
Judge for yourself.
Run your own prompts against IBM Granite 4.2 30B and Mistral Small 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about IBM Granite 4.2 30B vs Mistral Small 4.