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XHToken · Chat and reasoning · 4.11B parameters · Apache-2.0

Spark-X2.6-4B

Needs 5 GB at FP8 / INT8. The smallest real configuration today is 1× Quadro P2000 at Vast.ai, $0.03 per hour, about $22 a month at 730 hours.

Parameters4.11Bdense
Context1M tokensmaximum published
Checkpoint8 GBBF16, as published
LicenseApache-2.0check before commercial use
ReleasedOct 20, 2026documented date
Smallest configuration · FP8 / INT8
1× Quadro P20005 GB VRAM · 99% used
Per hour
$0.03
Per month
$22
Cheapest at
Vast.ai
All Quadro P2000 offers →

What is documented about Spark-X2.6-4B

news checked 2026-10-27

Compact on-device model with the same architecture as Spark-X2.5-4B and improved post-training (card). 27 sliding + 9 full-attention layers; 1M context. Secondary sources describe XHToken as an iFlytek subsidiary and date the announcement 2026-10-20; HF first commit 2026-10-19. #4 on HF trending.

  • https://huggingface.co/XHToken/Spark-X2.6-4B
  • https://huggingface.co/XHToken/Spark-X2.6-4B/raw/main/config.json
  • https://huggingface.co/api/models/XHToken/Spark-X2.6-4B?blobs=true
Memory · 3 precisions · 6 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 context1M context
BF16published checkpoint8 GB10 GB11 GB12 GB15 GB20 GB49 GB
FP8 / INT8estimated4 GB5 GB6 GB7 GB10 GB15 GB44 GB
INT4 / MXFP4estimated2 GB3 GB4 GB5 GB8 GB13 GB42 GB
KV cacheone sequence, FP16 cache, included above——1 GB2 GB5 GB10 GB39 GB
Cross-checked on Hugging Face Oct 28, 2026: 4.11B parameters in the safetensors headers, 8.2 GB of weight files, attention layout from config.json (36 layers, 4 KV heads × 256, 27 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 × 9 full-attention layers + 27 sliding-window layers capped at 512 tokens (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
Quadro P2000Best fit1× 5 GB5 GB total99% tight$0.03$22Vast.aiTrust 78 · read Nov 2 · receipt
RTX 30601× 12 GB12 GB total41%$0.04$26Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.05, gcube $0.05
RTX A20001× 12 GB12 GB total41%$0.04$26Vast.aiTrust 78 · read Nov 2 · receipt · also gcube $0.09, Runpod $0.12
GTX 1660 Ti1× 6 GB6 GB total82%$0.04$26Vast.aiTrust 78 · read Nov 2 · receipt · also Theta EdgeCloud $0.12
Tesla P41× 8 GB8 GB total62%$0.04$29Vast.aiTrust 78 · read Nov 2 · receipt · also Akash Network $0.06, gcube $0.07
T41× 16 GB16 GB total31%$0.04$29Vast.aiTrust 78 · read Nov 2 · receipt · also iwinv $0.20, Theta EdgeCloud $0.20
GTX 10601× 6 GB6 GB total82%$0.04$30Vast.aiTrust 78 · read Nov 2 · receipt
GTX 16601× 6 GB6 GB total82%$0.04$30Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.78
Tesla P401× 24 GB24 GB total21%$0.04$30Clore.aiTrust 49 · read Nov 2 · receipt · also gcube $0.07, Vast.ai $0.11
GTX Titan X1× 12 GB12 GB total41%$0.04$31Vast.aiTrust 78 · read Nov 2 · receipt
Titan Xp1× 12 GB12 GB total41%$0.04$31Vast.aiTrust 78 · read Nov 2 · receipt
GTX 10801× 8 GB8 GB total62%$0.04$32Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.06
Tesla P1001× 16 GB16 GB total31%$0.04$33Vast.aiTrust 78 · read Nov 2 · receipt · also gcube $0.07
RTX 20601× 6 GB6 GB total82%$0.04$33gcubenot scored · read Nov 2 · receipt · also Vast.ai $0.06, Edgevana $0.08
GTX 10701× 8 GB8 GB total62%$0.05$36Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.08
GTX 1660 Super1× 6 GB6 GB total82%$0.05$38Theta EdgeCloudnot scored · read Nov 2 · receipt
Quadro P40001× 8 GB8 GB total62%$0.06$40Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $0.08
RTX 20701× 8 GB8 GB total62%$0.06$41Vast.aiTrust 78 · read Nov 2 · receipt · also gcube $0.06, Clore.ai $0.21
RTX 3060 Ti1× 8 GB8 GB total62%$0.06$41Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.06, gcube $0.06
RTX 2060 Super1× 8 GB8 GB total62%$0.06$41gcubenot scored · read Nov 2 · receipt · also Clore.ai $0.06, Vast.ai $0.07
GTX 1070 Ti1× 8 GB8 GB total62%$0.06$44Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.10
RTX 2070 Super1× 8 GB8 GB total62%$0.06$44gcubenot scored · read Nov 2 · receipt · also Vast.ai $0.06, Edgevana $0.11
RTX 30701× 8 GB8 GB total62%$0.06$44gcubenot scored · read Nov 2 · receipt · also Clore.ai $0.07, Theta EdgeCloud $0.08
RTX 40601× 8 GB8 GB total62%$0.06$45Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.08, Theta EdgeCloud $0.09
The 24 cheapest of 106 GPU types that fit. Every GPU, any precision and context, in the finder