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Gemini 3.7 Flash vs Particle-1

Gemini 3.7 Flash leads the LLM Stats Score 47.2 to 32.0. Particle-1 is 3.4x cheaper per token.

Google · Particle AI · Updated for 2026

Which is better?

Gemini 3.7 Flash leads the overall LLM Stats Score 47.2 to 32.0, ranking #39 overall.

On price, Particle-1 is roughly 3.4x 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 Gemini 3.7 Flash

  • overall performance matters — it scores 47.2 and ranks #39 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes

Choose Particle-1

  • cost matters — it's about 3.4x 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.

Core performance indexes
47.2
#39
32.0
#135
44.5
#47
31.2
#137
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.75 / M
$0.25 / M
Output price
$3.75 / M
$1.00 / M
Context window
1,000,000
1,048,576

Individual benchmarks

19 reported for Gemini 3.7 Flash · 3 for Particle-1

No common benchmarks found

Gemini 3.7 Flash and Particle-1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Particle-1 costs less

For input processing, Gemini 3.7 Flash ($0.75/1M tokens) is 3.0x more expensive than Particle-1 ($0.25/1M tokens).

For output processing, Gemini 3.7 Flash ($3.75/1M tokens) is 3.8x more expensive than Particle-1 ($1.00/1M tokens).

In conclusion, Gemini 3.7 Flash is more expensive than Particle-1.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Nov 07 2026 • llm-stats.com
Google
Gemini 3.7 Flash
Input tokens$0.75
Output tokens$3.75
Best providerDeepinfra
Particle AI
Particle-1
Input tokens$0.25
Output tokens$1.00
Best providerUnknown Organization
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Particle-1 accepts 1,048,576 input tokens compared to Gemini 3.7 Flash's 1,000,000 tokens. Gemini 3.7 Flash can generate longer responses up to 1,000,000 tokens, while Particle-1 is limited to 131,072 tokens.

Google
Gemini 3.7 Flash
Input1,000,000 tokens
Output1,000,000 tokens
Particle AI
Particle-1
Input1,048,576 tokens
Output131,072 tokens
Sat Nov 07 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemini 3.7 Flash and Particle-1 support multimodal inputs.

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

Gemini 3.7 Flash

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 3.7 Flash

Proprietary

Closed source

Particle-1

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 3.7 Flash was released on 2026-08-13, while Particle-1 was released on 2026-10-28.

Particle-1 is 3 months newer than Gemini 3.7 Flash.

Gemini 3.7 Flash

Aug 13, 2026

2 months ago

Particle-1

Oct 28, 2026

1 weeks ago

2mo newer

Knowledge Cutoff

When training data ends

Gemini 3.7 Flash has a documented knowledge cutoff of 2026-03-31, while Particle-1's cutoff date is not specified.

We can confirm Gemini 3.7 Flash's training data extends to 2026-03-31, but cannot make a direct comparison without Particle-1's cutoff date.

Gemini 3.7 Flash

Mar 2026

Particle-1

—

Provider Availability

Gemini 3.7 Flash is available from DeepInfra, Google. Particle-1 is available from Particle AI.

Gemini 3.7 Flash

deepinfra logo
Deepinfra
Input Price:Input: $0.75/1MOutput Price:Output: $3.75/1M
google logo
Google
Input Price:Input: $0.75/1MOutput Price:Output: $3.75/1M

Particle-1

particle-ai logo
Unknown Organization
Input Price:Input: $0.25/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Gemini 3.7 Flash and Particle-1 side-by-side, then vote on the output you prefer.

Gemini 3.7 Flash
✓ Preferred
Particle-1
Open in Playground

FAQ

Common questions about Gemini 3.7 Flash vs Particle-1.

Which is better, Gemini 3.7 Flash or Particle-1?

Gemini 3.7 Flash leads the LLM Stats Score 47.2 to 32.0. Gemini 3.7 Flash 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 3.7 Flash compare to Particle-1 in benchmarks?

Gemini 3.7 Flash scores MRCR v2 (8-needle): 97.0%, Harvey LAB-AA: 90.7%, CharXiv-R: 88.7%, Terminal-Bench 2.1: 85.8%, LVBench: 85.4%. Particle-1 scores GPQA: 90.4%, BabyVision: 89.2%, MMLU: 86.1%.

Is Gemini 3.7 Flash cheaper than Particle-1?

Particle-1 is 3.0x cheaper for input tokens. Gemini 3.7 Flash costs $0.75/M input and $3.75/M output via deepinfra. Particle-1 costs $0.25/M input and $1.00/M output via particle-ai.

What are the context window sizes for Gemini 3.7 Flash and Particle-1?

Gemini 3.7 Flash supports 1.0M 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 3.7 Flash and Particle-1?

Key differences include LLM Stats Score (47.2 vs 32.0), context window (1.0M vs 1.0M), input pricing ($0.75 vs $0.25/M). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3.7 Flash and Particle-1?

Gemini 3.7 Flash is developed by Google and Particle-1 is developed by Particle AI.