Google · Chat and reasoning · 25.8B parameters · 4B active · apache-2.0
gemma 4 26B A4B it
Needs 31 GB at FP8 / INT8. The smallest real configuration today is 1× Tesla V100 32GB at Vast.ai, $0.07 per hour, about $50 a month at 730 hours.
Parameters25.8B4B active per token
Context256k tokensmaximum published
Checkpoint52 GBBF16, as published
Licenseapache-2.0check before commercial use
ReleasedApr 2, 2026documented date
Smallest configuration · FP8 / INT8
1× Tesla V100 32GB32 GB VRAM · 97% used
- Per hour
- $0.07
- Per month
- $50
- 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 | 256k context |
|---|---|---|---|---|---|---|
| BF16published checkpoint | 52 GB | 62 GB | 63 GB | 64 GB | 68 GB | 73 GB |
| FP8 / INT8estimated | 26 GB | 31 GB | 32 GB | 33 GB | 37 GB | 42 GB |
| INT4 / MXFP4estimated | 15 GB | 19 GB | 19 GB | 21 GB | 25 GB | 30 GB |
| KV cacheone sequence, FP16 cache, included above | — | — | 1 GB | 2 GB | 6 GB | 11 GB |
Cross-checked on Hugging Face Oct 28, 2026: 25.8B parameters in the safetensors headers, 51.6 GB of weight files, attention layout from config.json (30 layers, 8 KV heads × 256, 25 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 × 5 full-attention layers + 25 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 | 1× 32 GB32 GB total | 97% tight | $0.07 | $50 | |
| T4 | 2× 16 GB32 GB total | 97% tight | $0.08 | $59 | |
| Tesla P100 | 2× 16 GB32 GB total | 97% tight | $0.10 | $70 | |
| RTX A4000 | 2× 16 GB32 GB total | 97% tight | $0.14 | $105 | |
| RTX PRO 2000 | 2× 16 GB32 GB total | 97% tight | $0.15 | $106 | |
| Tesla V100 16GB | 2× 16 GB32 GB total | 97% tight | $0.16 | $118 | |
| RTX 3060 | 4× 12 GB48 GB total | 65% | $0.16 | $119 | |
| RTX 5060 Ti | 2× 16 GB32 GB total | 97% tight | $0.19 | $137 | |
| Quadro RTX 5000 | 2× 16 GB32 GB total | 97% tight | $0.20 | $148 | |
| RTX 3090 | 2× 24 GB48 GB total | 65% | $0.21 | $157 | |
| GTX 1080 | 4× 8 GB32 GB total | 97% tight | $0.22 | $157 | |
| RTX 2070 | 4× 8 GB32 GB total | 97% tight | $0.22 | $157 | |
| RTX 3060 Ti | 4× 8 GB32 GB total | 97% tight | $0.22 | $159 | |
| GTX 1070 Ti | 4× 8 GB32 GB total | 97% tight | $0.23 | $169 | |
| RTX 5090 | 1× 32 GB32 GB total | 97% tight | $0.24 | $172 | |
| RTX 2070 Super | 4× 8 GB32 GB total | 97% tight | $0.24 | $177 | |
| Quadro RTX 8000 | 1× 48 GB48 GB total | 65% | $0.25 | $186 | |
| RTX 6000 | 2× 24 GB48 GB total | 65% | $0.27 | $196 | |
| Titan RTX | 2× 24 GB48 GB total | 65% | $0.27 | $196 | |
| Titan Xp | 4× 12 GB48 GB total | 65% | $0.27 | $196 | |
| L40 | 1× 48 GB48 GB total | 65% | $0.27 | $196 | |
| RTX 2080 Ti | 4× 11 GB44 GB total | 70% | $0.28 | $202 | |
| RTX 3070 | 4× 8 GB32 GB total | 97% tight | $0.29 | $213 | |
| RTX 4070 Ti Super | 2× 16 GB32 GB total | 97% tight | $0.30 | $216 | |
| The 24 cheapest of 83 GPU types that fit. Every GPU, any precision and context, in the finder | |||||
Tokens per second, and what a million costs
Chat and reasoning. 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 |
|---|---|---|---|---|
| RTX 4090 | 2 | FP8 | 68.3 | $0.088 |
| MI300X | 1 | FP8 | 165 | $0.116 |
| RTX 5090 | 2 | FP8 | 88.9 | $0.123 |
| L40S | 1 | FP8 | 74.8 | $0.141 |
| H100 SXM | 1 | FP8 | 170 | $0.147 |
| H200 | 1 | FP8 | 195 | $0.156 |
| RTX PRO 6000 | 1 | FP8 | 124 | $0.157 |
| B200 | 1 | FP8 | 261 | $0.163 |
| H100 PCIe | 1 | FP8 | 128 | $0.163 |
| A100 80GB | 1 | BF16 | 84.8 | $0.229 |
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: RTX 4090Why estimates, and their limits →
