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NAVER · Chat and reasoning · 33.3B parameters · other

HyperCLOVAX SEED Think 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.

Parameters33.3Bdense
Context128k tokensmaximum published
Checkpoint67 GBBF16, as published
Licenseothercheck 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
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 context128k context
BF16published checkpoint67 GB80 GB82 GB90 GB119 GB
FP8 / INT8estimated33 GB40 GB42 GB50 GB79 GB
INT4 / MXFP4estimated20 GB24 GB26 GB34 GB63 GB
KV cacheone sequence, FP16 cache, included above——2 GB10 GB39 GB
Cross-checked on Hugging Face Oct 28, 2026: 33.3B parameters in the safetensors headers, 66.6 GB of weight files, attention layout from config.json (72 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 × 72 full-attention layers (FP16 cache, one sequence).config.json ↗
Smallest configuration per GPU · 109 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 total62%$0.14$99Vast.aiTrust 78 · read Nov 2 · receipt · also Cyfuture AI $1.13, io.net $2.52
RTX 30604× 12 GB48 GB total83%$0.16$118Clore.aiTrust 49 · read Nov 2 · receipt · also Vast.ai $0.21, Edgevana $0.31
Tesla P1004× 16 GB64 GB total62%$0.19$142Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.43
RTX 30902× 24 GB48 GB total83%$0.21$157Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.24, Lium $0.44
Quadro RTX 80001× 48 GB48 GB total83%$0.23$167Vast.aiTrust 78 · read Nov 2 · receipt · also TensorDock $0.32
Titan RTX2× 24 GB48 GB total83%$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.52
Titan Xp4× 12 GB48 GB total83%$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt
L401× 48 GB48 GB total83%$0.27$196Vast.aiTrust 78 · read Nov 2 · receipt · also io.net $0.66, Runpod $0.69
RTX 2080 Ti4× 11 GB44 GB total91% tight$0.28$202Vast.aiTrust 78 · read Nov 2 · receipt
RTX A60001× 48 GB48 GB total83%$0.33$241GPURentonot scored · read Nov 2 · receipt · also gcube $0.34, Thunder Compute $0.35
RTX 4000 Ada2× 20 GB40 GB total100% tight$0.35$254Vast.aiTrust 78 · read Nov 2 · receipt · also iwinv $0.57, Akamai Cloud $1.05
A401× 48 GB48 GB total83%$0.35$255GPURentonot scored · read Nov 2 · receipt · also Vast.ai $0.48, Exoscale $1.05
RTX 60002× 24 GB48 GB total83%$0.35$256Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.40
RTX 5060 Ti4× 16 GB64 GB total62%$0.35$258Clore.aiTrust 49 · read Nov 2 · receipt · also Vast.ai $0.40, Edgevana $0.68
RTX A40004× 16 GB64 GB total62%$0.36$266Vast.aiTrust 78 · read Nov 2 · receipt · also AtmosCompute $0.66, Spheron $3.84
RTX 30804× 10 GB40 GB total100% tight$0.38$274Clore.aiTrust 49 · read Nov 2 · receipt · also Vast.ai $0.51, Edgevana $1.23
RTX A50002× 24 GB48 GB total83%$0.38$274Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.74, Airon AI $0.90
RTX 4070 Super4× 12 GB48 GB total83%$0.38$274Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.58, AtmosCompute $0.69
Tesla V100 16GB4× 16 GB64 GB total62%$0.38$275Vast.aiTrust 78 · read Nov 2 · receipt · also CloudRift $1.00, AtmosCompute $1.30
A100 40GB1× 40 GB40 GB total100% tight$0.39$283Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.58, AtmosCompute $0.73
RTX 6000 Ada1× 48 GB48 GB total83%$0.40$290gcubenot scored · read Nov 2 · receipt · also Vast.ai $0.50, GPU.ai $0.65
RTX PRO 50001× 48 GB48 GB total83%$0.40$294Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.57, Clore.ai $0.63
Quadro RTX 50004× 16 GB64 GB total62%$0.40$294Vast.aiTrust 78 · read Nov 2 · receipt
RTX 3090 Ti2× 24 GB48 GB total83%$0.42$304Clore.aiTrust 49 · read Nov 2 · receipt · also Vast.ai $0.48, Edgevana $0.59
The 24 cheapest of 72 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
MI300X1FP866.5$0.277
B2001FP8117$0.360
H100 SXM1FP857.5$0.363
H100 PCIe1FP836.8$0.394
H2001FP876.4$0.399
RTX PRO 60001FP833.6$0.404
RTX 50902FP840.9$0.464
RTX 40902FP826.0$0.778
L40S1FP817.1$1.00
A100 80GB1BF1620.3$3.11
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 →