Google · Vision · 27.4B parameters · other
medgemma-27b-it
Needs 33 GB at FP8 / INT8. The smallest real configuration today is 2× Tesla V100 32GB at Vast.ai, $0.14 per hour, about $99 a month at 730 hours.
Parameters27.4Bdense
Context128k tokensmaximum published
Checkpoint55 GBBF16, as published
Licenseothercheck before commercial use
Released—documented date
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 51% used
- Per hour
- $0.14
- Per month
- $99
- Cheapest at
Vast.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 | 55 GB | 66 GB | 67 GB | 69 GB | 78 GB |
| FP8 / INT8estimated | 27 GB | 33 GB | 34 GB | 36 GB | 45 GB |
| INT4 / MXFP4estimated | 16 GB | 20 GB | 21 GB | 23 GB | 31 GB |
| KV cacheone sequence, FP16 cache, included above | — | — | 1 GB | 4 GB | 12 GB |
Cross-checked on Hugging Face Oct 28, 2026: 27.4B parameters in the safetensors headers, 54.9 GB of weight files, attention layout from config.json (62 layers, 16 KV heads × 128, 52 sliding-window layers). 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 × 10 full-attention layers + 52 sliding-window layers capped at 1024 tokens (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 V100 32GBBest fit | 2× 32 GB64 GB total | 51% | $0.14 | $99 | |
| RTX 3060 | 4× 12 GB48 GB total | 69% | $0.16 | $118 | |
| Tesla P100 | 4× 16 GB64 GB total | 51% | $0.19 | $142 | |
| RTX 3090 | 2× 24 GB48 GB total | 69% | $0.21 | $157 | |
| Quadro RTX 8000 | 1× 48 GB48 GB total | 69% | $0.23 | $167 | |
| Titan RTX | 2× 24 GB48 GB total | 69% | $0.27 | $196 | |
| Titan Xp | 4× 12 GB48 GB total | 69% | $0.27 | $196 | |
| L40 | 1× 48 GB48 GB total | 69% | $0.27 | $196 | |
| RTX 2080 Ti | 4× 11 GB44 GB total | 75% | $0.28 | $202 | |
| RTX A6000 | 1× 48 GB48 GB total | 69% | $0.33 | $241 | |
| RTX 4000 Ada | 2× 20 GB40 GB total | 82% | $0.35 | $254 | |
| A40 | 1× 48 GB48 GB total | 69% | $0.35 | $255 | |
| RTX 6000 | 2× 24 GB48 GB total | 69% | $0.35 | $256 | |
| RTX 5060 Ti | 4× 16 GB64 GB total | 51% | $0.35 | $258 | |
| RTX A4000 | 4× 16 GB64 GB total | 51% | $0.36 | $266 | |
| RTX 3080 | 4× 10 GB40 GB total | 82% | $0.38 | $274 | |
| RTX A5000 | 2× 24 GB48 GB total | 69% | $0.38 | $274 | |
| RTX 4070 Super | 4× 12 GB48 GB total | 69% | $0.38 | $274 | |
| Tesla V100 16GB | 4× 16 GB64 GB total | 51% | $0.38 | $275 | |
| A100 40GB | 1× 40 GB40 GB total | 82% | $0.39 | $283 | |
| RTX 6000 Ada | 1× 48 GB48 GB total | 69% | $0.40 | $290 | |
| RTX PRO 5000 | 1× 48 GB48 GB total | 69% | $0.40 | $294 | |
| Quadro RTX 5000 | 4× 16 GB64 GB total | 51% | $0.40 | $294 | |
| RTX 3090 Ti | 2× 24 GB48 GB total | 69% | $0.42 | $304 | |
| The 24 cheapest of 72 GPU types that fit. Every GPU, any precision and context, in the finder | |||||
Tokens per second, and what a million costs
Vision. Speed estimated from memory bandwidth and model size, never measured. The cost per 1M output tokens is an estimate at the prices read on Oct 4, 2026; it is not recomputed here.
| GPU | Cards | Precision | tok/s per user | per 1M output tokens · estimate |
|---|---|---|---|---|
| MI300X | 1 | FP8 | 76.3 | $0.218 |
| RTX 4090 | 2 | FP8 | 30.1 | $0.242 |
| H100 SXM | 1 | FP8 | 66.2 | $0.274 |
| B200 | 1 | FP8 | 133 | $0.285 |
| H100 PCIe | 1 | FP8 | 42.4 | $0.292 |
| RTX 5090 | 2 | FP8 | 47.1 | $0.295 |
| L40S | 1 | FP8 | 19.7 | $0.301 |
| RTX PRO 6000 | 1 | FP8 | 38.8 | $0.314 |
| H200 | 1 | FP8 | 87.6 | $0.317 |
| A100 80GB | 1 | BF16 | 23.5 | $0.660 |
cards, precision and speed estimated from memory bandwidth and model size; cost recomputed by the site from verified prices · cheapest per output at the prices of Oct 4, 2026: MI300XWhy estimates, and their limits →
