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Models / gemma-3
5 models (270M to 27B) · ↓ 6.1M downloads a month · from $0.08/h on GTX 1660 SUPER right now. Each model's versions do the same job; quantized ones (AWQ, FP8, 4-bit) need less GPU memory and run on cheaper machines.
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| Originalgoogle/gemma-3-270mLicence to accept | vLLM | 540 MB | ~2.9 GB | $0.10/h RTX 3060 |
| itgoogle/gemma-3-270m-itLicence to accept | vLLM | 540 MB | ~2.9 GB | $0.10/h RTX 3060 |
| it unsloth bnb 4bit (unsloth)unsloth/gemma-3-270m-it-unsloth-bnb-4bit | vLLM | 390 MB | 2.8 GB | $0.10/h RTX 3060 |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| Originalgoogle/gemma-3-1b-ptLicence to accept | vLLM | 2.0 GB | ~4.6 GB | $0.10/h RTX 3060 |
| gemma 3 1b itgoogle/gemma-3-1b-itLicence to accept | vLLM | 2.0 GB | ~4.6 GB | $0.10/h RTX 3060 |
| gemma 3 1b it unsloth bnb 4bit (unsloth)unsloth/gemma-3-1b-it-unsloth-bnb-4bit | vLLM | 1.0 GB | 3.6 GB | $0.10/h RTX 3060 |
| gemma 3 1b instruct onnx genai int4 emb int8 (Arm)Arm/gemma-3-1b-instruct-onnx-genai-int4-emb-int8 | ONNX Runtime GenAI | 910 MB | 2.7 GB | $0.08/h GTX 1660 SUPER |
| gemma 3 1b base onnx genai int4 emb int8 (Arm)Arm/gemma-3-1b-base-onnx-genai-int4-emb-int8 | ONNX Runtime GenAI | 900 MB | 2.6 GB | $0.08/h GTX 1660 SUPER |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| Originalgoogle/gemma-3-4b-ptLicence to accept | vLLM | 8.6 GB | ~12.5 GB | $0.14/h RTX A4000 |
| gemma 3 4b itgoogle/gemma-3-4b-itLicence to accept | vLLM | 8.6 GB | ~12.5 GB | $0.14/h RTX A4000 |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| Originalgoogle/gemma-3-12b-ptLicence to accept | vLLM | 24 GB | ~31.5 GB | $0.41/h RTX PRO 4500 |
| gemma 3 12b itgoogle/gemma-3-12b-itLicence to accept | vLLM | 24 GB | ~31.5 GB | $0.41/h RTX PRO 4500 |
| gemma 3 12b it quantized W4A16 (abhishekchohan)abhishekchohan/gemma-3-12b-it-quantized-W4A16 | vLLM | 8.4 GB | 15.1 GB | $0.14/h RTX A4000 |
| gemma 3 12b it int4 awq (gaunernst)gaunernst/gemma-3-12b-it-int4-awq | vLLM | 9.1 GB | 15.7 GB | $0.14/h RTX A4000 |
| gemma 3 12b it heretic v2 (DreamFast)DreamFast/gemma-3-12b-it-heretic-v2 | vLLM | 24 GB | 32.9 GB | $0.45/h Nvidia A40 |
| gemma 3 12b it heretic (DreamFast)DreamFast/gemma-3-12b-it-heretic | vLLM | 24 GB | 32.9 GB |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| gemma 3 27b itgoogle/gemma-3-27b-itLicence to accept | vLLM | 55 GB | ~68.1 GB | $0.89/h 2x Nvidia A40 |
| medgemma 27b itgoogle/medgemma-27b-itLicence to accept | vLLM | 55 GB | ~68.1 GB | $0.89/h 2x Nvidia A40 |
| medgemma 27b text itgoogle/medgemma-27b-text-itLicence to accept | vLLM | 54 GB | ~67 GB | $0.89/h 2x Nvidia A40 |
| gemma 3 27b it int4 awq (gaunernst)gaunernst/gemma-3-27b-it-int4-awq | vLLM | 18 GB | 27.4 GB | $0.34/h 2x RTX 5060 Ti |
| gemma 3 27b it GPTQ 4b 128g (ISTA-DASLab)ISTA-DASLab/gemma-3-27b-it-GPTQ-4b-128g | vLLM | 17 GB | 25.6 GB | $0.34/h 2x RTX 5060 Ti |
| gemma 3 27b it quantized.w4a16 (RedHatAI)RedHatAI/gemma-3-27b-it-quantized.w4a16 | vLLM | 20 GB |
Model details come from Hugging Face and are refreshed daily; prices follow the live offers. GPU memory is GridPup's estimate: the weights, room for an 8,192-token conversation (chat models) and the runtime's own memory. Large models are split across the GPUs of one machine ("4x RTX 4090").
| $0.45/h Nvidia A40 |
| 28.7 GB |
| $0.34/h 2x RTX 5060 Ti |
| gemma 3 27b it FP8 dynamic (RedHatAI)RedHatAI/gemma-3-27b-it-FP8-dynamic | vLLM | 29 GB | 39.4 GB | $0.45/h Nvidia A40 |