Gemini 1.5 Pro vs Particle-1
Particle-1 leads the LLM Stats Score 31.9 to 11.5. Particle-1 is 10.0x cheaper per token.
Google · Particle AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 11.5, ranking #133 overall.
In the 2 individual benchmarks reported for both models, Particle-1 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Particle-1 is roughly 10.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 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 1.5 Pro
- you process long inputs — it offers a 2,097,152 token context window
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
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 10.0x cheaper per token
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
23 reported for Gemini 1.5 Pro · 3 for Particle-1
Gemini 1.5 Pro outperforms in 0 benchmarks, while Particle-1 is better at 2 benchmarks (GPQA, MMLU).
Particle-1 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 1.5 Pro ($2.50/1M tokens) is 10.0x more expensive than Particle-1 ($0.25/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 10.0x more expensive than Particle-1 ($1.00/1M tokens).
In conclusion, Gemini 1.5 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
Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Particle-1's 1,048,576 tokens. Particle-1 can generate longer responses up to 131,072 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 1.5 Pro and Particle-1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 1.5 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 1.5 Pro was released on 2024-05-01, while Particle-1 was released on 2026-10-28.
Particle-1 is 30 months newer than Gemini 1.5 Pro.
May 1, 2024
2.5 years ago
Oct 28, 2026
-1 days ago
2.5yr newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Particle-1's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Particle-1's cutoff date.
Nov 2023
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Provider Availability
Gemini 1.5 Pro is available from Google. Particle-1 is available from Particle AI.
Gemini 1.5 Pro
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs Particle-1.