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Qwen · Chat and reasoning · 35B parameters · 3B active · apache-2.0

Qwen3.6 35B-A3B

Needs 48 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.

Parameters35B3B active per token
Context256k tokensmaximum published
Checkpoint72 GBBF16, as published
Licenseapache-2.0check before commercial use
Released—documented date
Downloads4,415,423Qwen/Qwen3.6-35B-A3B ↗
Smallest configuration · FP8 / INT8
2× Tesla V100 32GB64 GB VRAM · 74% used
Per hour
$0.14
Per month
$99
Cheapest at
Vast.ai
All Tesla V100 32GB offers →
Memory · 3 precisions · 5 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 context128k context256k context
BF16published checkpoint72 GB87 GB87 GB89 GB98 GB108 GB
FP8 / INT8published checkpoint40 GB48 GB48 GB51 GB59 GB69 GB
INT4 / MXFP4published checkpoint23 GB28 GB28 GB31 GB39 GB50 GB
KV cacheone sequence, FP16 cache, included above——1 GB3 GB11 GB22 GB
Cross-checked on Hugging Face Oct 28, 2026: 36.0B parameters in the safetensors headers, 71.9 GB of weight files, attention layout from config.json (40 layers, 2 KV heads × 256). 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 = 2048 bytes per token per layer × 40 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 total74%$0.14$99Vast.aiTrust 78 · read Nov 2 · receipt · also Cyfuture AI $1.13, io.net $2.52
RTX 30604× 12 GB48 GB total99% tight$0.16$118Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.21, Edgevana $0.31
Tesla P1004× 16 GB64 GB total74%$0.19$142Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.43
RTX 30902× 24 GB48 GB total99% tight$0.21$157Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.24, Lium $0.44
Quadro RTX 80001× 48 GB48 GB total99% tight$0.23$167Vast.aiTrust 78 · read Nov 2 · receipt · also TensorDock $0.32
Titan RTX2× 24 GB48 GB total99% tight$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.52
Titan Xp4× 12 GB48 GB total99% tight$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt
L401× 48 GB48 GB total99% tight$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt · also io.net $0.66, Runpod $0.69
RTX A60001× 48 GB48 GB total99% tight$0.33$241GPURentonot scored · read Nov 2 · receipt · also gcube $0.34, Thunder Compute $0.35
A401× 48 GB48 GB total99% tight$0.35$255GPURentonot scored · read Nov 2 · receipt · also Vast.ai $0.48, Exoscale $1.05
RTX 60002× 24 GB48 GB total99% tight$0.35$256Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.40
RTX 5060 Ti4× 16 GB64 GB total74%$0.35$258Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.40, Edgevana $0.68
RTX A40004× 16 GB64 GB total74%$0.36$266Vast.aiTrust 78 · read Nov 2 · receipt · also AtmosCompute $0.66, Spheron $3.84
RTX A50002× 24 GB48 GB total99% tight$0.38$274Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.74, Airon AI $0.90
RTX 4070 Super4× 12 GB48 GB total99% tight$0.38$274Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.58, AtmosCompute $0.69
Tesla V100 16GB4× 16 GB64 GB total74%$0.38$275Vast.aiTrust 78 · read Nov 2 · receipt · also CloudRift $1.00, AtmosCompute $1.30
RTX 6000 Ada1× 48 GB48 GB total99% tight$0.40$290gcubenot scored · read Nov 2 · receipt · also Vast.ai $0.50, GPU.ai $0.65
RTX PRO 50001× 48 GB48 GB total99% tight$0.40$294Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.57, Clore.ai $0.63
Quadro RTX 50004× 16 GB64 GB total74%$0.40$294Vast.aiTrust 78 · read Nov 2 · receipt
RTX 3090 Ti2× 24 GB48 GB total99% tight$0.42$304Clore.aiTrust 46 · read Nov 2 · receipt · also Vast.ai $0.48, Edgevana $0.59
L40S1× 48 GB48 GB total99% tight$0.42$304Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.50, GPUBank $0.55
RTX PRO 40002× 24 GB48 GB total99% tight$0.45$332Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.62, Clore.ai $0.75
A800 80GB PCIe1× 80 GB80 GB total59%$0.47$342Vast.aiTrust 78 · read Nov 2 · receipt
A102× 24 GB48 GB total99% tight$0.48$352Vast.aiTrust 78 · read Nov 2 · receipt · also Volcano Engine $3.19, Microsoft Azure $6.52
The 24 cheapest of 73 GPU types that fit. Every GPU, any precision and context, in the finder
Throughput estimates · Oct 4, 2026

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.

GPUCardsPrecisiontok/s per userper 1M output tokens · estimate
RTX 40902FP861.9$0.107
MI300X1FP8151$0.137
RTX 50902FP877.2$0.141
L40S1FP884.6$0.167
H100 SXM1FP8166$0.173
H2001FP8182$0.181
RTX PRO 60001FP8131$0.183
B2001FP8240$0.192
H100 PCIe1FP8132$0.193
A100 80GB2BF1678.8$0.344
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 →