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LG AI Research · Chat and reasoning · 749B parameters · 37B active · apache-2.0

K-EXAONE 2.0 750B A37B

Needs 899 GB at FP8 / INT8. The smallest real configuration today is 4× MI325X at Cyfuture AI, $12.29 per hour, about $8,972 a month at 730 hours.

Parameters749B37B active per token
Context256k tokensmaximum published
Checkpoint1,499 GBBF16, as published
Licenseapache-2.0check before commercial use
ReleasedJul 31, 2026documented date
Smallest configuration · FP8 / INT8
4× MI325X1024 GB VRAM · 88% used
Per hour
$12.29
Per month
$8,972
Cheapest at
Cyfuture AI
All MI325X 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 checkpoint1,499 GB1,799 GB1,800 GB1,809 GB1,841 GB1,883 GB
FP8 / INT8estimated749 GB899 GB901 GB910 GB941 GB983 GB
INT4 / MXFP4estimated449 GB540 GB541 GB550 GB582 GB624 GB
KV cacheone sequence, FP16 cache, included above——2 GB11 GB42 GB84 GB
Cross-checked on Hugging Face Oct 28, 2026: 749.4B parameters in the safetensors headers, 1498.7 GB of weight files, attention layout from config.json (78 layers, 8 KV heads × 128, 58 sliding-window layers). 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 × 20 full-attention layers + 58 sliding-window layers capped at None tokens (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
MI325XBest fit4× 256 GB1024 GB total88%$12.29$8,972Cyfuture AInot scored · read Nov 2 · receipt
MI300X8× 192 GB1536 GB total59%$13.68$9,986TensorWaveTrust 64 · read Nov 2 · receipt · also Cyfuture AI $22.38, AtmosCompute $26.77
H2008× 141 GB1128 GB total80%$21.04$15,359Airon AInot scored · read Nov 2 · receipt · also Geodd $21.76, Lium $23.92
B3004× 288 GB1152 GB total78%$23.29$17,004UpCloudTrust 75 · read Nov 2 · receipt · also FPT AI Factory $27.96, Verda $45.40
MI355X8× 288 GB2304 GB total39%$23.60$17,228TensorWaveTrust 64 · read Nov 2 · receipt
H200 NVL8× 141 GB1128 GB total80%$26.09$19,042IONOSnot scored · read Nov 2 · receipt · also Geodd $27.12, Vast.ai $39.47
B2008× 180 GB1440 GB total62%$32.91$24,026UpCloudTrust 75 · read Nov 2 · receipt · also Airon AI $33.04, Deep Infra $39.12
B300 CC4× 288 GB1152 GB total78%$46.31$33,806VerdaTrust 81 · read Nov 2 · receipt
GB3004× 288 GB1152 GB total78%$52.21$38,113VerdaTrust 81 · read Nov 2 · receipt
B200 CC8× 180 GB1440 GB total62%$72.37$52,830VerdaTrust 81 · read Nov 2 · receipt
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
MI300X8FP826.8$4.57
H2008FP834.9$5.56
B2008FP846.8$6.08
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 →