Google · Chat and reasoning · 12.2B parameters · gemma
Gemma 3 12B
Needs 17 GB at FP8 / INT8. The smallest real configuration today is 1× Tesla P40 at Clore.ai, $0.04 per hour, about $30 a month at 730 hours.
Parameters12.2Bdense
Context128k tokensmaximum published
Checkpoint24 GBBF16, as published
Licensegemmacheck before commercial use
Released—documented date
Smallest configuration · FP8 / INT8
1× Tesla P4024 GB VRAM · 67% used
- Per hour
- $0.04
- Per month
- $30
- Cheapest at
Clore.ai
How much VRAM it needs
Weights plus runtime overhead, then the KV cache that grows with the context you serve.
| Precision | Weights | Weights + headroom | 4k context | 32k context | 128k context |
|---|---|---|---|---|---|
| BF16published checkpoint | 24 GB | 30 GB | 31 GB | 43 GB | 81 GB |
| FP8 / INT8published checkpoint | 13 GB | 17 GB | 18 GB | 29 GB | 68 GB |
| INT4 / MXFP4published checkpoint | 8 GB | 10 GB | 11 GB | 23 GB | 61 GB |
| KV cacheone sequence, FP16 cache, included above | — | — | 2 GB | 13 GB | 52 GB |
Cross-checked on Hugging Face Oct 28, 2026: 12.2B parameters in the safetensors headers, 24.4 GB of weight files, attention layout from config.json (48 layers, 8 KV heads × 256). Method: weights as published at the native precision, verified on Hugging Face 2026-10-28; other precisions estimated at 1 (8-bit) and 0.6 (4-bit) bytes per parameter; × 1.2 runtime headroom; KV cache = 8192 bytes per token per layer × 48 full-attention layers (FP16 cache, one sequence).config.json ↗
What it costs to run, GPU by GPU
The fewest GPUs of one type whose total memory fits the model at short context, priced from the cheapest eligible on-demand offer for exactly that count (45-day window, newest reading per provider), with the next providers beside it. Monthly = 730 hours.
| GPU | Smallest config | VRAM used | $ / hour | $ / month | Cheapest at |
|---|---|---|---|---|---|
| Tesla P40Best fit | 1× 24 GB24 GB total | 67% | $0.04 | $30 | |
| RTX A2000 | 2× 12 GB24 GB total | 67% | $0.07 | $50 | |
| RTX 3060 | 2× 12 GB24 GB total | 67% | $0.07 | $50 | |
| Tesla V100 32GB | 1× 32 GB32 GB total | 50% | $0.07 | $50 | |
| Tesla M40 | 1× 24 GB24 GB total | 67% | $0.07 | $54 | |
| GTX 1080 Ti | 2× 11 GB22 GB total | 73% | $0.08 | $55 | |
| T4 | 2× 16 GB32 GB total | 50% | $0.08 | $59 | |
| RTX 3090 | 1× 24 GB24 GB total | 67% | $0.09 | $66 | |
| Tesla P100 | 2× 16 GB32 GB total | 50% | $0.10 | $70 | |
| L4 | 1× 24 GB24 GB total | 67% | $0.10 | $76 | |
| Quadro P2000 | 4× 5 GB20 GB total | 80% | $0.11 | $80 | |
| RTX A4500 | 1× 20 GB20 GB total | 80% | $0.11 | $82 | |
| RTX A5000 | 1× 24 GB24 GB total | 67% | $0.12 | $87 | |
| Titan Xp | 2× 12 GB24 GB total | 67% | $0.12 | $89 | |
| RTX 2060 | 4× 6 GB24 GB total | 67% | $0.12 | $91 | |
| RTX 4090 | 1× 24 GB24 GB total | 67% | $0.13 | $94 | |
| RTX 6000 | 1× 24 GB24 GB total | 67% | $0.13 | $98 | |
| Titan RTX | 1× 24 GB24 GB total | 67% | $0.14 | $99 | |
| RTX 3090 Ti | 1× 24 GB24 GB total | 67% | $0.14 | $104 | |
| RTX 2080 Ti | 2× 11 GB22 GB total | 73% | $0.14 | $104 | |
| RTX A4000 | 2× 16 GB32 GB total | 50% | $0.14 | $105 | |
| RTX PRO 2000 | 2× 16 GB32 GB total | 50% | $0.15 | $106 | |
| RTX 3080 | 2× 10 GB20 GB total | 80% | $0.16 | $120 | |
| RTX 4000 Ada | 1× 20 GB20 GB total | 80% | $0.17 | $128 | |
| The 24 cheapest of 91 GPU types that fit. Every GPU, any precision and context, in the finder | |||||
