Mid-tier Gemma. Strong general-purpose chat model at small scale. The Gemma Terms of Use permit commercial use subject to Google's prohibited-use policy.
- Parameters
- 9B
- Context length
- 8K
- Modality
- text
- Released
- 2024-06-27
Memory & hardware
- VRAM (fp16)
- 18 GB
- VRAM (Q4)
- 5.4 GB
- Recommended
- RTX 3090 24GB
- Quantizations
- fp16, q8_0, q5_k_m, q4_k_m
Benchmarks
Hosted inference pricing
USD per million tokens.
| Provider | Input | Output | |
|---|---|---|---|
| groqCheapest | $0.20 | $0.20 |
Run it yourself
Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.
ollama run gemma2:9b
vllm serve google/gemma-2-9b-it
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b-it")
model = AutoModelForCausalLM.from_pretrained(
"google/gemma-2-9b-it", device_map="auto", torch_dtype="auto"
)google/gemma-2-9b-it Related models
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- License
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- Context
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- License
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- License
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- License
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- Context
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- License
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