Mistral Small vs Particle-1
Comparing Mistral Small and Particle-1 across benchmarks, pricing, and capabilities.
Mistral AI · Particle AI · Updated for 2026
Which is better?
Mistral Small and Particle-1 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Mistral Small is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Particle-1 also accepts a larger context window (1,048,576 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 Mistral Small
- cost matters — it's about 1.5x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Particle-1
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
0 reported for Mistral Small · 3 for Particle-1
Mistral Small and Particle-1don'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, Mistral Small ($0.20/1M tokens) is 1.3x cheaper than Particle-1 ($0.25/1M tokens).
For output processing, Mistral Small ($0.60/1M tokens) is 1.7x cheaper than Particle-1 ($1.00/1M tokens).
In conclusion, Particle-1 is more expensive than Mistral Small.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Particle-1 accepts 1,048,576 input tokens compared to Mistral Small's 32,768 tokens. Particle-1 can generate longer responses up to 131,072 tokens, while Mistral Small is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas Mistral Small does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Small
Particle-1
License
Usage and distribution terms
Mistral Small is licensed under Mistral Research License, while Particle-1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Mistral Research License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Mistral Small was released on 2024-09-17, while Particle-1 was released on 2026-10-28.
Particle-1 is 26 months newer than Mistral Small.
Sep 17, 2024
2.1 years ago
Oct 28, 2026
-3 days ago
2.1yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Mistral Small is available from Mistral AI. Particle-1 is available from Particle AI.
Mistral Small
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Small and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Small vs Particle-1.