Command R+ vs Mistral Small 3.1 24B Base
Command R+ and Mistral Small 3.1 24B Base are closely matched at -0.5 and 0.3 on the LLM Stats Score. Mistral Small 3.1 24B Base is 2.9x cheaper per token.
Cohere · Mistral AI · Updated for 2026
Which is better?
Command R+ and Mistral Small 3.1 24B Base are closely matched on the overall LLM Stats Score at -0.5 and 0.3.
In the 1 individual benchmarks reported for both models, Mistral Small 3.1 24B Base wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Mistral Small 3.1 24B Base is roughly 2.9x 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 Command R+
- you want predictable pricing at $0.25/M input and $1.00/M output
Choose Mistral Small 3.1 24B Base
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 2.9x 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
6 reported for Command R+ · 5 for Mistral Small 3.1 24B Base
Command R+ outperforms in 0 benchmarks, while Mistral Small 3.1 24B Base is better at 1 benchmark (MMLU).
Mistral Small 3.1 24B Base 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, Command R+ ($0.25/1M tokens) is 2.5x more expensive than Mistral Small 3.1 24B Base ($0.10/1M tokens).
For output processing, Command R+ ($1.00/1M tokens) is 3.3x more expensive than Mistral Small 3.1 24B Base ($0.30/1M tokens).
In conclusion, Command R+ 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
Command R+ has 80.0B more parameters than Mistral Small 3.1 24B Base, making it 333.3% 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
Mistral Small 3.1 24B Base supports multimodal inputs, whereas Command R+ does not.
Mistral Small 3.1 24B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.
Command R+
Mistral Small 3.1 24B Base
License
Usage and distribution terms
Command R+ is licensed under CC BY-NC, 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.
CC BY-NC
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Command R+ was released on 2024-08-30, while Mistral Small 3.1 24B Base was released on 2025-03-17.
Mistral Small 3.1 24B Base is 7 months newer than Command R+.
Aug 30, 2024
2.1 years ago
Mar 17, 2025
1.6 years ago
6mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Command R+ is available from Cohere, Bedrock. Mistral Small 3.1 24B Base is available from Mistral AI.
Command R+
Mistral Small 3.1 24B Base
Outputs Comparison
Judge for yourself.
Run your own prompts against Command R+ and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.
FAQ
Common questions about Command R+ vs Mistral Small 3.1 24B Base.