Gemma 3 27B vs Mistral Small 3.1 24B Base
Gemma 3 27B and Mistral Small 3.1 24B Base are closely matched at 8.3 and 0.3 on the LLM Stats Score. Gemma 3 27B is 1.5x cheaper per token.
Google · Mistral AI · Updated for 2026
Which is better?
Gemma 3 27B and Mistral Small 3.1 24B Base are closely matched on the overall LLM Stats Score at 8.3 and 0.3.
In the 2 individual benchmarks reported for both models, Gemma 3 27B wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 3 27B is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemma 3 27B also accepts a larger context window (131,072 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 Gemma 3 27B
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.5x cheaper per token
- you process long inputs — it offers a 131,072 token context window
Choose Mistral Small 3.1 24B Base
- 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
27 reported for Gemma 3 27B · 5 for Mistral Small 3.1 24B Base
Gemma 3 27B outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Mistral Small 3.1 24B Base is better at 0 benchmarks.
Gemma 3 27B 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, Gemma 3 27B ($0.08/1M tokens) is 1.3x cheaper than Mistral Small 3.1 24B Base ($0.10/1M tokens).
For output processing, Gemma 3 27B ($0.16/1M tokens) is 1.9x cheaper than Mistral Small 3.1 24B Base ($0.30/1M tokens).
In conclusion, Mistral Small 3.1 24B Base is more expensive than Gemma 3 27B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Gemma 3 27B has 3.0B more parameters than Mistral Small 3.1 24B Base, making it 12.5% larger.
Context Window
Maximum input and output token capacity
Gemma 3 27B accepts 131,072 input tokens compared to Mistral Small 3.1 24B Base's 128,000 tokens. Gemma 3 27B can generate longer responses up to 131,072 tokens, while Mistral Small 3.1 24B Base is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 3 27B and Mistral Small 3.1 24B Base support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3 27B
Mistral Small 3.1 24B Base
License
Usage and distribution terms
Gemma 3 27B is licensed under Gemma, 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.
Gemma
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemma 3 27B was released on 2025-03-12, while Mistral Small 3.1 24B Base was released on 2025-03-17.
Mistral Small 3.1 24B Base is 0 month newer than Gemma 3 27B.
Mar 12, 2025
1.5 years ago
Mar 17, 2025
1.5 years ago
5d newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Gemma 3 27B is available from DeepInfra, Novita. Mistral Small 3.1 24B Base is available from Mistral AI.
Gemma 3 27B
Mistral Small 3.1 24B Base
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 27B and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 27B vs Mistral Small 3.1 24B Base.