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Qwen · Chat and reasoning · 32.8B parameters · apache-2.0

Qwen3 32B

Needs 44 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
Context40k tokensmaximum published
Checkpoint66 GBBF16, as published
Licenseapache-2.0check before commercial use
Released—documented date
Downloads2,872,589Qwen/Qwen3-32B ↗
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 68% used
Per hour
$0.14
Per month
$99
Cheapest at
Vast.ai
All Tesla V100 32GB offers →
Memory · 3 precisions · 4 context lengths

How much VRAM it needs

Weights plus runtime overhead, then the KV cache that grows with the context you serve.

PrecisionWeightsWeights + headroom4k context32k context40k context
BF16published checkpoint66 GB79 GB80 GB88 GB90 GB
FP8 / INT8published checkpoint36 GB44 GB45 GB52 GB54 GB
INT4 / MXFP4published checkpoint21 GB26 GB27 GB34 GB36 GB
KV cacheone sequence, FP16 cache, included above——2 GB9 GB11 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 ↗
Smallest configuration per GPU · 110 GPUs · cheapest eligible on-demand offer per GPU count, every provider on file

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.

GPUSmallest configVRAM used$ / hour$ / monthCheapest at
Tesla V100 32GBBest fit2× 32 GB64 GB total68%$0.14$99Vast.aiTrust 78 · read Nov 1 · receipt · also Cyfuture AI $1.13, io.net $2.52
T44× 16 GB64 GB total68%$0.16$117Vast.aiTrust 78 · read Nov 1 · receipt · also iwinv $0.78, NHN Cloud $2.46
RTX 30604× 12 GB48 GB total90% tight$0.16$119Clore.aiTrust 46 · read Nov 1 · receipt · also Vast.ai $0.21, Edgevana $0.37
Tesla P1004× 16 GB64 GB total68%$0.19$138Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.37
RTX 30902× 24 GB48 GB total90% tight$0.21$157Vast.aiTrust 78 · read Nov 1 · receipt · also Clore.ai $0.24, Edgevana $0.46
Quadro RTX 80001× 48 GB48 GB total90% tight$0.25$186Vast.aiTrust 78 · read Nov 1 · receipt · also TensorDock $0.32
RTX 60002× 24 GB48 GB total90% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt
Titan RTX2× 24 GB48 GB total90% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.55
Titan Xp4× 12 GB48 GB total90% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt
L401× 48 GB48 GB total90% tight$0.27$196Vast.aiTrust 78 · read Nov 1 · receipt · also io.net $0.66, GPURento $0.69
RTX 2080 Ti4× 11 GB44 GB total98% tight$0.28$202Vast.aiTrust 78 · read Nov 1 · receipt
RTX A60001× 48 GB48 GB total90% tight$0.33$241GPURentonot scored · read Nov 1 · receipt · also gcube $0.34, Thunder Compute $0.35
A401× 48 GB48 GB total90% tight$0.35$255GPURentonot scored · read Nov 1 · receipt · also Vast.ai $0.48, Exoscale $1.05
RTX 5060 Ti4× 16 GB64 GB total68%$0.35$258Clore.aiTrust 46 · read Nov 1 · receipt · also Vast.ai $0.38, Edgevana $0.68
RTX A40004× 16 GB64 GB total68%$0.36$266Vast.aiTrust 78 · read Nov 1 · receipt · also Spheron $3.84
RTX A50002× 24 GB48 GB total90% tight$0.38$274Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.74, Airon AI $0.90
RTX 4070 Super4× 12 GB48 GB total90% tight$0.38$274Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.56, Clore.ai $0.58
Tesla V100 16GB4× 16 GB64 GB total68%$0.38$275Vast.aiTrust 78 · read Nov 1 · receipt · also CloudRift $1.00, AtmosCompute $1.30
RTX 6000 Ada1× 48 GB48 GB total90% tight$0.40$290gcubenot scored · read Nov 1 · receipt · also Vast.ai $0.50, GPU.ai $0.65
Quadro RTX 50004× 16 GB64 GB total68%$0.40$294Vast.aiTrust 78 · read Nov 1 · receipt
RTX 3090 Ti2× 24 GB48 GB total90% tight$0.42$304Clore.aiTrust 46 · read Nov 1 · receipt
L40S1× 48 GB48 GB total90% tight$0.43$314Vast.aiTrust 78 · read Nov 1 · receipt · also Clore.ai $0.50, GPUBank $0.55
RTX PRO 40002× 24 GB48 GB total90% tight$0.45$332Vast.aiTrust 78 · read Nov 1 · receipt · also Edgevana $0.62, Clore.ai $0.75
A800 80GB PCIe1× 80 GB80 GB total54%$0.47$342Vast.aiTrust 78 · read Nov 1 · receipt
The 24 cheapest of 74 GPU types that fit. Every GPU, any precision and context, in the finder
Throughput estimates · internal study · 2026-10-04

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 the study's own estimate at the prices it read on 2026-10-04; it is not recomputed here.

GPUCardsPrecisiontok/s per userper 1M output tokens · study estimate
MI300X1FP868.8$0.266
H100 SXM1FP859.2$0.338
B2001FP8121$0.346
H100 PCIe1FP837.7$0.365
H2001FP878.9$0.384
RTX PRO 60001FP834.4$0.388
RTX 50902FP842.7$0.420
RTX 40902FP827.0$0.633
L40S1FP817.4$0.806
A100 80GB1BF1620.8$2.09
cards, precision and speed estimated from memory bandwidth and model size (internal study); cost recomputed by the site from verified prices · cheapest per output at study prices: MI300XWhy estimates, and their limits →