Gemini 3.1 Pro vs Particle-1
Gemini 3.1 Pro leads the LLM Stats Score 42.9 to 32.0. Particle-1 is 10.3x cheaper per token.
Google · Particle AI · Updated for 2026
Which is better?
Gemini 3.1 Pro leads the overall LLM Stats Score 42.9 to 32.0, ranking #61 overall.
In the 1 individual benchmarks reported for both models, Gemini 3.1 Pro wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Particle-1 is roughly 10.3x 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 Gemini 3.1 Pro
- overall performance matters — it scores 42.9 and ranks #61 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
Choose Particle-1
- cost matters — it's about 10.3x 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
21 reported for Gemini 3.1 Pro · 3 for Particle-1
Gemini 3.1 Pro outperforms in 1 benchmarks (GPQA), while Particle-1 is better at 0 benchmarks.
Gemini 3.1 Pro 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, Gemini 3.1 Pro ($2.00/1M tokens) is 8.0x more expensive than Particle-1 ($0.25/1M tokens).
For output processing, Gemini 3.1 Pro ($12.00/1M tokens) is 12.0x more expensive than Particle-1 ($1.00/1M tokens).
In conclusion, Gemini 3.1 Pro 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 Gemini 3.1 Pro's 1,000,000 tokens. Gemini 3.1 Pro can generate longer responses up to 1,000,000 tokens, while Particle-1 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 3.1 Pro and Particle-1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 3.1 Pro
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
Gemini 3.1 Pro was released on 2026-02-19, while Particle-1 was released on 2026-10-28.
Particle-1 is 8 months newer than Gemini 3.1 Pro.
Feb 19, 2026
8 months ago
Oct 28, 2026
1 weeks ago
8mo newerKnowledge Cutoff
When training data ends
Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while Particle-1's cutoff date is not specified.
We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without Particle-1's cutoff date.
Jan 2025
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Provider Availability
Gemini 3.1 Pro is available from DeepInfra, Google. Particle-1 is available from Particle AI.
Gemini 3.1 Pro
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 3.1 Pro and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 3.1 Pro vs Particle-1.