Gemma 3 4B vs Particle-1
Particle-1 leads the LLM Stats Score 31.9 to -2.4. Gemma 3 4B is 17.5x cheaper per token.
Google · Particle AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to -2.4, 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.
On price, Gemma 3 4B is roughly 17.5x 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 Gemma 3 4B
- cost matters — it's about 17.5x cheaper per token
- you need open weights you can self-host or fine-tune
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 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
26 reported for Gemma 3 4B · 3 for Particle-1
Gemma 3 4B outperforms in 0 benchmarks, while Particle-1 is better at 1 benchmark (GPQA).
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, Gemma 3 4B ($0.02/1M tokens) is 12.5x cheaper than Particle-1 ($0.25/1M tokens).
For output processing, Gemma 3 4B ($0.04/1M tokens) is 25.0x cheaper than Particle-1 ($1.00/1M tokens).
In conclusion, Particle-1 is more expensive than Gemma 3 4B.*
* 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 Gemma 3 4B's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 3 4B and Particle-1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3 4B
Particle-1
License
Usage and distribution terms
Gemma 3 4B is licensed under Gemma, while Particle-1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Gemma
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 3 4B was released on 2025-03-12, while Particle-1 was released on 2026-10-28.
Particle-1 is 20 months newer than Gemma 3 4B.
Mar 12, 2025
1.6 years ago
Oct 28, 2026
2 days ago
1.6yr newerKnowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while Particle-1's cutoff date is not specified.
We can confirm Gemma 3 4B's training data extends to 2024-08-01, but cannot make a direct comparison without Particle-1's cutoff date.
Aug 2024
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Provider Availability
Gemma 3 4B is available from DeepInfra. Particle-1 is available from Particle AI.
Gemma 3 4B
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 4B and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 4B vs Particle-1.