DeepSeek · Chat and reasoning · 32.8B parameters · mit
DeepSeek R1 Distill Qwen 32B
Needs 40 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.
Parameters32.8Bdense
Context128k tokensmaximum published
Checkpoint66 GBBF16, as published
Licensemitcheck before commercial use
Released—documented date
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 62% 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 | 66 GB | 79 GB | 80 GB | 88 GB | 113 GB |
| FP8 / INT8estimated | 33 GB | 40 GB | 41 GB | 48 GB | 74 GB |
| INT4 / MXFP4estimated | 20 GB | 24 GB | 25 GB | 33 GB | 58 GB |
| KV cacheone sequence, FP16 cache, included above | — | — | 2 GB | 9 GB | 35 GB |
Cross-checked on Hugging Face Oct 28, 2026: 32.8B parameters in the safetensors headers, 65.5 GB of weight files, attention layout from config.json (64 layers, 8 KV heads × 128). 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 = 4096 bytes per token per layer × 64 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 V100 32GBBest fit | 2× 32 GB64 GB total | 62% | $0.14 | $99 | |
| T4 | 4× 16 GB64 GB total | 62% | $0.16 | $117 | |
| RTX 3060 | 4× 12 GB48 GB total | 82% | $0.16 | $119 | |
| Tesla P100 | 4× 16 GB64 GB total | 62% | $0.19 | $138 | |
| RTX 3090 | 2× 24 GB48 GB total | 82% | $0.21 | $157 | |
| Quadro RTX 8000 | 1× 48 GB48 GB total | 82% | $0.25 | $186 | |
| RTX 6000 | 2× 24 GB48 GB total | 82% | $0.27 | $196 | |
| Titan RTX | 2× 24 GB48 GB total | 82% | $0.27 | $196 | |
| Titan Xp | 4× 12 GB48 GB total | 82% | $0.27 | $196 | |
| L40 | 1× 48 GB48 GB total | 82% | $0.27 | $196 | |
| RTX 2080 Ti | 4× 11 GB44 GB total | 89% | $0.28 | $202 | |
| RTX A6000 | 1× 48 GB48 GB total | 82% | $0.33 | $241 | GPURentonot scored · read Nov 1 · receipt · also gcube $0.34, Thunder Compute $0.35 |
| A100 40GB | 1× 40 GB40 GB total | 98% tight | $0.34 | $246 | |
| A40 | 1× 48 GB48 GB total | 82% | $0.35 | $255 | GPURentonot scored · read Nov 1 · receipt · also Vast.ai $0.48, Exoscale $1.05 |
| RTX 5060 Ti | 4× 16 GB64 GB total | 62% | $0.35 | $258 | |
| RTX A4000 | 4× 16 GB64 GB total | 62% | $0.36 | $266 | |
| RTX 3080 | 4× 10 GB40 GB total | 98% tight | $0.38 | $274 | |
| RTX A5000 | 2× 24 GB48 GB total | 82% | $0.38 | $274 | |
| RTX 4070 Super | 4× 12 GB48 GB total | 82% | $0.38 | $274 | |
| Tesla V100 16GB | 4× 16 GB64 GB total | 62% | $0.38 | $275 | |
| RTX 6000 Ada | 1× 48 GB48 GB total | 82% | $0.40 | $290 | |
| Quadro RTX 5000 | 4× 16 GB64 GB total | 62% | $0.40 | $294 | |
| RTX 3090 Ti | 2× 24 GB48 GB total | 82% | $0.42 | $304 | |
| L40S | 1× 48 GB48 GB total | 82% | $0.43 | $314 | |
| The 24 cheapest of 74 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 |
|---|---|---|---|---|
| MI300X | 1 | FP8 | 68.8 | $0.266 |
| H100 SXM | 1 | FP8 | 59.2 | $0.338 |
| B200 | 1 | FP8 | 121 | $0.346 |
| H100 PCIe | 1 | FP8 | 37.7 | $0.365 |
| H200 | 1 | FP8 | 78.9 | $0.384 |
| RTX PRO 6000 | 1 | FP8 | 34.4 | $0.388 |
| RTX 5090 | 2 | FP8 | 42.7 | $0.420 |
| RTX 4090 | 2 | FP8 | 27.0 | $0.633 |
| L40S | 1 | FP8 | 17.4 | $0.806 |
| A100 80GB | 1 | BF16 | 20.8 | $2.09 |
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 →
