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Gemini 2.0 Flash Thinking vs Particle-1

Particle-1 leads the LLM Stats Score 31.9 to 16.1.

Google · Particle AI · Updated for 2026

Which is better?

Particle-1 leads the overall LLM Stats Score 31.9 to 16.1, ranking #133 overall.

In the 1 individual benchmarks reported for both models, Particle-1 wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 2.0 Flash Thinking

  • you are already invested in the Google ecosystem

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 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Core performance indexes
16.1
#255
31.9
#133
16.4
#248
31.2
#135
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
— / M
$0.25 / M
Output price
— / M
$1.00 / M
Context window
—
1,048,576

Individual benchmarks

3 reported for Gemini 2.0 Flash Thinking · 3 for Particle-1

1 shared

Gemini 2.0 Flash Thinking outperforms in 0 benchmarks, while Particle-1 is better at 1 benchmark (GPQA).

Particle-1 significantly outperforms across most benchmarks.

Fri Oct 30 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Particle-1 specifies input context (1,048,576 tokens). Only Particle-1 specifies output context (131,072 tokens).

Google
Gemini 2.0 Flash Thinking
Input- tokens
Output- tokens
Particle AI
Particle-1
Input1,048,576 tokens
Output131,072 tokens
Fri Oct 30 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 2.0 Flash Thinking and Particle-1 support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 2.0 Flash Thinking

Text
Images
Audio
Video

Particle-1

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Gemini 2.0 Flash Thinking

Proprietary

Closed source

Particle-1

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 2.0 Flash Thinking was released on 2025-01-21, while Particle-1 was released on 2026-10-28.

Particle-1 is 22 months newer than Gemini 2.0 Flash Thinking.

Gemini 2.0 Flash Thinking

Jan 21, 2025

1.8 years ago

Particle-1

Oct 28, 2026

-3 days ago

1.8yr newer

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash Thinking has a documented knowledge cutoff of 2024-08-01, while Particle-1's cutoff date is not specified.

We can confirm Gemini 2.0 Flash Thinking's training data extends to 2024-08-01, but cannot make a direct comparison without Particle-1's cutoff date.

Gemini 2.0 Flash Thinking

Aug 2024

Particle-1

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Gemini 2.0 Flash Thinking and Particle-1 side-by-side, then vote on the output you prefer.

Gemini 2.0 Flash Thinking
✓ Preferred
Particle-1
Open in Playground

FAQ

Common questions about Gemini 2.0 Flash Thinking vs Particle-1.

Which is better, Gemini 2.0 Flash Thinking or Particle-1?

Particle-1 leads the LLM Stats Score 31.9 to 16.1. Gemini 2.0 Flash Thinking is made by Google and Particle-1 is made by Particle AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 2.0 Flash Thinking compare to Particle-1 in benchmarks?

Gemini 2.0 Flash Thinking scores MMMU: 75.4%, GPQA: 74.2%, AIME 2024: 73.3%. Particle-1 scores GPQA: 90.4%, BabyVision: 89.2%, MMLU: 86.1%.

What are the context window sizes for Gemini 2.0 Flash Thinking and Particle-1?

Gemini 2.0 Flash Thinking supports an unknown number of tokens and Particle-1 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 2.0 Flash Thinking and Particle-1?

Key differences include LLM Stats Score (16.1 vs 31.9). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.0 Flash Thinking and Particle-1?

Gemini 2.0 Flash Thinking is developed by Google and Particle-1 is developed by Particle AI.