NVIDIA · Chat and reasoning · 11.1B parameters · openmdw-1.1
NVIDIA NemotronLabs VoiceChat 11B
Needs 14 GB at FP8 / INT8. The smallest real configuration today is 1× T4 at Vast.ai, $0.04 per hour, about $29 a month at 730 hours.
Parameters11.1Bdense
Context—maximum published
Checkpoint44 GBFP32, as published
Licenseopenmdw-1.1check before commercial use
Released—documented date
Smallest configuration · FP8 / INT8
1× T416 GB VRAM · 83% used
- Per hour
- $0.04
- Per month
- $29
- Cheapest at
Vast.ai
How much VRAM it needs
Weights plus runtime overhead. The context dimension appears once the model's architecture is on file.
| Precision | Weights | Weights + headroom |
|---|---|---|
| FP32published checkpoint | 44 GB | 54 GB |
| FP8 / INT8estimated | 11 GB | 14 GB |
| INT4 / MXFP4estimated | 7 GB | 8 GB |
Cross-checked on Hugging Face Oct 28, 2026: 11.1B parameters in the safetensors headers, 44.4 GB of weight files. 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 not added (architecture not readable).
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 |
|---|---|---|---|---|---|
| T4Best fit | 1× 16 GB16 GB total | 83% | $0.04 | $29 | |
| Tesla P40 | 1× 24 GB24 GB total | 56% | $0.04 | $30 | |
| Tesla P100 | 1× 16 GB16 GB total | 83% | $0.04 | $33 | |
| Tesla V100 16GB | 1× 16 GB16 GB total | 83% | $0.06 | $46 | |
| RTX A2000 | 2× 12 GB24 GB total | 56% | $0.07 | $50 | |
| RTX 3060 | 2× 12 GB24 GB total | 56% | $0.07 | $50 | |
| Tesla V100 32GB | 1× 32 GB32 GB total | 42% | $0.07 | $50 | |
| RTX PRO 2000 | 1× 16 GB16 GB total | 83% | $0.07 | $51 | |
| RTX A4000 | 1× 16 GB16 GB total | 83% | $0.07 | $53 | |
| Tesla M40 | 1× 24 GB24 GB total | 56% | $0.07 | $54 | |
| GTX 1080 Ti | 2× 11 GB22 GB total | 61% | $0.08 | $55 | |
| RTX 3060 Ti | 2× 8 GB16 GB total | 83% | $0.08 | $61 | |
| RTX 5060 Ti | 1× 16 GB16 GB total | 83% | $0.08 | $61 | |
| RTX 3090 | 1× 24 GB24 GB total | 56% | $0.09 | $66 | |
| GTX 1070 | 2× 8 GB16 GB total | 83% | $0.10 | $70 | |
| GTX 1080 | 2× 8 GB16 GB total | 83% | $0.10 | $76 | |
| L4 | 1× 24 GB24 GB total | 56% | $0.10 | $76 | |
| GTX 1070 Ti | 2× 8 GB16 GB total | 83% | $0.11 | $79 | |
| RTX 2070 | 2× 8 GB16 GB total | 83% | $0.11 | $79 | |
| Quadro P2000 | 4× 5 GB20 GB total | 67% | $0.11 | $80 | |
| Quadro P4000 | 2× 8 GB16 GB total | 83% | $0.11 | $81 | |
| RTX A4500 | 1× 20 GB20 GB total | 67% | $0.11 | $82 | |
| RTX A5000 | 1× 24 GB24 GB total | 56% | $0.12 | $87 | |
| Titan Xp | 2× 12 GB24 GB total | 56% | $0.12 | $89 | |
| The 24 cheapest of 98 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 | 1 | FP8 | 54.6 | $0.121 |
| MI300X | 1 | FP8 | 155 | $0.123 |
| RTX 5090 | 1 | FP8 | 89.3 | $0.127 |
| L40S | 1 | FP8 | 47.5 | $0.148 |
| H100 SXM | 1 | FP8 | 141 | $0.156 |
| B200 | 1 | FP8 | 252 | $0.167 |
| H100 PCIe | 1 | FP8 | 95.7 | $0.170 |
| H200 | 1 | FP8 | 177 | $0.173 |
| RTX PRO 6000 | 1 | FP8 | 88.8 | $0.174 |
| A100 80GB | 1 | BF16 | 56.1 | $0.272 |
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 →
