o1 vs Particle-1
Particle-1 leads the LLM Stats Score 31.9 to 20.4. Particle-1 is 60.0x cheaper per token.
OpenAI · Particle AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 20.4, ranking #133 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Particle-1 is roughly 60.0x 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 o1
- you want predictable pricing at $15.00/M input and $60.00/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 60.0x 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
19 reported for o1 · 3 for Particle-1
o1 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, o1 ($15.00/1M tokens) is 60.0x more expensive than Particle-1 ($0.25/1M tokens).
For output processing, o1 ($60.00/1M tokens) is 60.0x more expensive than Particle-1 ($1.00/1M tokens).
In conclusion, o1 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 o1's 200,000 tokens. Particle-1 can generate longer responses up to 131,072 tokens, while o1 is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas o1 does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
o1
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
o1 was released on 2024-12-17, while Particle-1 was released on 2026-10-28.
Particle-1 is 23 months newer than o1.
Dec 17, 2024
1.9 years ago
Oct 28, 2026
1 days ago
1.9yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
o1 is available from Azure, OpenAI. Particle-1 is available from Particle AI.
o1
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against o1 and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about o1 vs Particle-1.