o3-mini vs Particle-1
Particle-1 leads the LLM Stats Score 31.9 to 20.8. Particle-1 is 4.4x cheaper per token.
OpenAI · Particle AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 20.8, ranking #133 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Particle-1 is roughly 4.4x 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 o3-mini
- you want predictable pricing at $1.10/M input and $4.40/M output
Choose Particle-1
- overall performance matters — it scores 31.9 and ranks #133 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 4.4x cheaper per token
- 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
25 reported for o3-mini · 3 for Particle-1
o3-mini outperforms in 1 benchmarks (MMLU), while Particle-1 is better at 1 benchmark (GPQA).
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, o3-mini ($1.10/1M tokens) is 4.4x more expensive than Particle-1 ($0.25/1M tokens).
For output processing, o3-mini ($4.40/1M tokens) is 4.4x more expensive than Particle-1 ($1.00/1M tokens).
In conclusion, o3-mini is more expensive than Particle-1.*
* 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 o3-mini's 200,000 tokens. Particle-1 can generate longer responses up to 131,072 tokens, while o3-mini is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas o3-mini does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
o3-mini
Particle-1
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
o3-mini was released on 2025-01-30, while Particle-1 was released on 2026-10-28.
Particle-1 is 21 months newer than o3-mini.
Jan 30, 2025
1.7 years ago
Oct 28, 2026
2 days ago
1.7yr newerKnowledge Cutoff
When training data ends
o3-mini has a documented knowledge cutoff of 2023-09-30, while Particle-1's cutoff date is not specified.
We can confirm o3-mini's training data extends to 2023-09-30, but cannot make a direct comparison without Particle-1's cutoff date.
Sep 2023
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Provider Availability
o3-mini is available from Azure, OpenAI. Particle-1 is available from Particle AI.
o3-mini
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against o3-mini and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about o3-mini vs Particle-1.