Gemma
Google's open models — Gemini's research, small enough to self-host.
Gemma is Google DeepMind's open-weight family, built from the same research as Gemini but published so you can download and run it. Sizes run from a few billion parameters up to about thirty, they read text and images, and the current line has a 256K context with a switchable thinking mode. The obvious starting point if you want a capable model on your own machine or on cheap hardware.
At a glance — Gemma 3 4B
- Cost
- $0.05 in · $0.10 out per 1M tokensBudget
- Memory
- 131K tokens — about 200 pages
- Reads
- Text · Images
- Can do
- Use tools (agents) (not supported)
- Structured output
- Thinking mode (not supported)
- Good at
- Coding: better than 0%
- Reliability
- 100.00% uptime, last 24h
- Released
- Mar 13, 2025
Advanced details
- API model ID
google/gemma-3-4b-it- Max output
- 16K tokens
- Knowledge cutoff
- 2024-08-31
- Tokenizer
- Gemini
- Coding index
- 2.7
Providers
The same model, hosted by different companies. OpenRouter picks one per request and falls back to the next if it fails.
| Provider | Input /1M | Output /1M | Cached /1M | Max output | Uptime 24h |
|---|---|---|---|---|---|
| DeepInfra · bf16 | $0.05 | $0.10 | — | 16K | 100.00% |
Supported parameters
- frequency_penalty
- logit_bias
- max_tokens
- min_p
- presence_penalty
- repetition_penalty
- response_format
- seed
- stop
- structured_outputs
- temperature
- top_k
- top_p
Live from OpenRouter, refreshed hourly. Scores from Artificial Analysis.
Key info
- Pricing
- Open source
- Category
- Models
- Best for
- Intermediate
- Made by
- Google DeepMind
- Weights
- Open
- Good for
- Running a capable model on your own machine