Gemma 3n E4B Instructed vs Mistral Small
Comparing Gemma 3n E4B Instructed and Mistral Small across benchmarks, pricing, and capabilities.
Google · Mistral AI · Updated for 2026
Which is better?
Gemma 3n E4B Instructed and Mistral Small trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Mistral Small is roughly 83.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Small also accepts a larger context window (32,768 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 3n E4B Instructed
- you want the most recent training data — it shipped Jun 2025
Choose Mistral Small
- cost matters — it's about 83.3x cheaper per token
- you process long inputs — it offers a 32,768 token context window
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
18 reported for Gemma 3n E4B Instructed · 0 for Mistral Small
Gemma 3n E4B Instructed and Mistral Smalldon'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, Gemma 3n E4B Instructed ($20.00/1M tokens) is 100.0x more expensive than Mistral Small ($0.20/1M tokens).
For output processing, Gemma 3n E4B Instructed ($40.00/1M tokens) is 66.7x more expensive than Mistral Small ($0.60/1M tokens).
In conclusion, Gemma 3n E4B Instructed is more expensive than Mistral Small.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Small has 14.0B more parameters than Gemma 3n E4B Instructed, making it 175.0% larger.
Context Window
Maximum input and output token capacity
Mistral Small accepts 32,768 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. Mistral Small can generate longer responses up to 32,768 tokens, while Gemma 3n E4B Instructed is limited to 32,000 tokens.
Input capabilities
Documented input modalities across available providers
Gemma 3n E4B Instructed supports multimodal inputs, whereas Mistral Small does not.
Gemma 3n E4B Instructed can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemma 3n E4B Instructed
Mistral Small
License
Usage and distribution terms
Gemma 3n E4B Instructed is licensed under a proprietary license, while Mistral Small uses Mistral Research License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Mistral Research License
Open weights
Release Timeline
When each model was launched
Gemma 3n E4B Instructed was released on 2025-06-26, while Mistral Small was released on 2024-09-17.
Gemma 3n E4B Instructed is 9 months newer than Mistral Small.
Jun 26, 2025
1.2 years ago
9mo newerSep 17, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while Mistral Small's cutoff date is not specified.
We can confirm Gemma 3n E4B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without Mistral Small's cutoff date.
Jun 2024
—
Provider Availability
Gemma 3n E4B Instructed is available from Together. Mistral Small is available from Mistral AI.
Gemma 3n E4B Instructed
Mistral Small
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3n E4B Instructed and Mistral Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3n E4B Instructed vs Mistral Small.