Google · language model
Gemma 3 12B: pricing, context and benchmarks
Gemma 3 12B is Google's model released on March 13, 2025. It costs $0.05 per million input tokens and $0.15 per million output tokens, with a 131.1K-token context window. Epoch AI ranks it #121 of 125 rated models.
| Performance (ECI) | 2/40 | |
|---|---|---|
| Price | 29/30 | |
| Context | 4/15 | |
| Features | 12/15 |
What you need to know about Gemma 3 12B
Google, based in United States, put Gemma 3 12B online on March 13, 2025. It accepts text and images as input and produces text. Its context window reaches 131,072 tokens, larger than 29 % of the models in the registry, and it can write up to 16,384 tokens in one go.
Released more than 1 year ago, it belongs to a generation most vendors have since superseded.
Gemma 3 12B pricing
On OpenRouter, Gemma 3 12B costs $0.05 per million input tokens and $0.15 per million output tokens. Counting three tokens read for every token written, its average price is $0.075 per million, more expensive than 5 % of paid models (10.2 times cheaper than the median of $0.76).
A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0002. At 1,000 tasks a day, budget $5 a month. The price calculator redoes this with your own volumes.
Performance and benchmarks
The Epoch Capabilities Index (ECI), which aggregates published results across many benchmarks, gives Gemma 3 12B a score of 123.5 (range 114.2 to 128.8). That places it #121 of 125 rated models.
Scores published by Epoch AI on the benchmarks the site tracks:
| Benchmark | What it measures | Score | Date |
|---|---|---|---|
| GPQA Diamond | PhD-level science questions | 39.5 % | Mar 12, 2025 |
| OTIS Mock AIME | maths competition problems | 16.7 % | Mar 12, 2025 |
For at least equal performance, gpt-oss-20b costs at least 30% less.
Features, privacy and local use
- It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
- It can answer in an enforced JSON format (structured outputs).
- Its knowledge stops at August 2024.
Its weights are open and downloadable from Hugging Face: you can run it on your own machines without sending your data to a third party.
Other Google models
| Model | Released | Avg. price | ECI |
|---|---|---|---|
| Gemini 4 Argon | Oct 13, 2026 | $4 | 166.5 |
| Nano Banana 2.1 | Oct 6, 2026 | $3 | — |
| Gemini 3.8 Flash | Sep 2, 2026 | $1.65 | 157.4 |
| Gemini 3.7 Flash | Aug 13, 2026 | $1.5 | 158 |
| Gemini 3.6 Flash | Jul 21, 2026 | $1.5 | 154.5 |
| Gemini 3.5 Flash Lite | Jul 21, 2026 | $0.85 | 144.9 |
| Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) | Jun 30, 2026 | $0.56 | — |
| Nano Banana 2 (Gemini 3.1 Flash Image) | Jun 18, 2026 | $1.13 | — |
Verdict
Computed score: 47/100, from public data (performance, price, context, features).
Strengths
- Low price: cheaper than 95 % of paid models.
- Open weights: self-hostable, your data stays with you.
- Agent-ready: tool calling and structured JSON output.
Limitations
- Modest performance: behind 96 % of rated models.
- Older generation, often replaced by a newer model from the same vendor.
Alternatives
- Mistral Nemo$0.03
- gpt-oss-20b$0.04
- Phi 4$0.09
- GPT-4o-mini$0.26
- GPT-4o-mini (2024-07-18)$0.26
- Qwen3 32B$0.13
Comparisons and tools
Learn more
Frequently asked questions
How much does Gemma 3 12B cost?
$0.05 per million input tokens and $0.15 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.0002.
How big is Gemma 3 12B's context window?
131,072 tokens, roughly 98,000 words, with a maximum of 16,384 output tokens.
Can Gemma 3 12B run locally?
Yes, its weights are published.
Is Gemma 3 12B suitable for an AI agent?
Technically yes: it supports tool calling and structured outputs. Then check its cost for your volume.
How good is Gemma 3 12B?
Epoch AI ranks it #121 of 125 rated models (ECI 123.5). On GPQA Diamond, it scores 39.5%.
What are the alternatives to Gemma 3 12B?
The closest models on price and performance are Mistral Nemo, gpt-oss-20b, and Phi 4.
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- LLM benchmarks: how to read model rankingsOctober 24, 2026
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score