Models › Huihui family

Huihui-Qwen3.8-27B-abliterated

huihui-ai Apache 2.0 out 2 months ago

27.8B parameters, images and text in, text out. 1 provider serves it.

Verified 2026-10-25 Rank #551 in LLMs · score 74.9 method v1 Sources 3 Downloads 30d 38.1k · #401 of 619 tracked

Changed this week: 2 new quantized builds on the Hub (92 in all).2026-10-24

Can I run it?17GB at INT4Estimatefits a 24 GB cardmethod
Can I use it?Apache 2.0Permissive; patent grantlicence file
Do people use it?38.1kdownloads, 30 days#401 of 619 we track · below the median+36 likes, downloads −9% this week617 likesHugging Face

Where to run it

Live hosted endpoints, cheapest first, USD per million tokens. Ties break on output price, then provider name.

#Cheapest live rowIn /1MOut /1MContextQuantSeen
1 Featherless — — — — Oct 25

All 1 provider →

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

Served by 1 API provider; heavily run locally (92 quantized builds).

  • As a service1Featherless
  • On own hardware92quantized builds
  • Built on2011 fine-tunes · 6 adapters · 3 merges
  • In apps0Hugging Face Spaces

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Fits a 64 GB Mac (unified memory) at INT4

About 17 GB at INT4, 33 GB at FP8, 67 GB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 17 GB of weights (estimate; KV cache and activations extra)INT417 GBFP8: about 33 GB of weights (estimate; KV cache and activations extra)FP833 GBBF16: about 67 GB of weights (estimate; KV cache and activations extra)BF1667 GB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 17 GB of weights (estimate; KV cache and activations extra)INT417 GBFP8: about 33 GB of weights (estimate; KV cache and activations extra)FP833 GBBF16: about 67 GB of weights (estimate; KV cache and activations extra)BF1667 GB

Estimate params × bytes per param × 1.2 · how we estimate

What people built on it

112 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

112 derivatives on the Hub, most of them quantized

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

92 quantized (Hugging Face model tree)11 fine-tunes (Hugging Face model tree)3 merges (Hugging Face model tree)6 adapters (Hugging Face model tree)92 quantized11 fine-tunes3 merges6 adapters
92 quantized (Hugging Face model tree)11 fine-tunes (Hugging Face model tree)3 merges (Hugging Face model tree)6 adapters (Hugging Face model tree)92 quantized11 fine-tunes3 merges6 adapters

All variants →

Reference

Everything else, folded: the full tables, every source.

Use-case evidence

2 use cases

What it is good at 2 use cases

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

14 fields

Listed in LLMs

Facts

Pipeline tagimage-text-to-text
Librarytransformers
ArchitecturesQwen3_5ForConditionalGeneration
Model typeqwen3_5
Params by dtypeBF16: 27,781,427,952
Size bandL
MoEno
LicenseApache 2.0 (apache-2.0)
Hub snapshot2026-10-25

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for Huihui-Qwen3.8-27B-abliterated: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)67 GB · Single high-end GPU (<80 GB)
FP8 (1 byte/param)33 GB · Single high-end GPU (<80 GB)
INT4 (0.5 bytes/param)17 GB · Single GPU (<24 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

All variants

40 variants

Lineage

Fine-tuned from Qwen/Qwen3.8-27B Family: huihui-ai/Huihui 112 derivatives on the Hub

Base model: Qwen/Qwen3.8-27B

quantized: 92finetune: 11merge: 3adapter: 6

Top variants (40 shown, ranked by downloads)

Relation
Quant
Size
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
LessThanThreeAI/Qwen3.8-27B-Humanlike-Chat-GGUF quantized GGUF — — apache-2.0 LessThanThreeAI 211 114.2k
sakamakismile/Huihui-Qwen3.8-27B-abliterated-NVFP4 quantized NVFP4 27.4B L apache-2.0 sakamakismile 66 102.4k
Barding-Defense/Qwen3.8-27B-huihui-abliterated-NVFP4-NInfer quantized NVFP4 — — apache-2.0 Barding-Defense 12 69.3k
RentedNoodle/Qwen3.8-27B-GSQ-RCO-IQ3_XXS-Uncensored quantized GGUF — — apache-2.0 RentedNoodle 67 51.8k
prithivMLmods/Qwen3.8-27B-abliterated-GGUF quantized GGUF — — apache-2.0 prithivMLmods 7 42.1k
mradermacher/Huihui-Qwen3.8-27B-abliterated-GGUF quantized GGUF — — apache-2.0 mradermacher 5 39.2k
Barding-Defense/Qwen3.8-27B-huihui-abliterated-groupwise-int-NInfer quantized — — — apache-2.0 Barding-Defense 1 37.8k
mradermacher/Huihui-Qwen3.8-27B-abliterated-i1-GGUF quantized GGUF — — apache-2.0 mradermacher 18 28.8k
TelperionAI/Huihui-Qwen3.8-27B-abliterated-INT4-AWQ-GPTQ quantized INT4 7.84B M apache-2.0 TelperionAI 7 25.3k
WaveCut/Huihui-Qwen3.8-27B-abliterated-NInfer-v3 quantized — — — apache-2.0 WaveCut 5 19.2k
lyf/Qwen3.8-27B-Huihui-Abliterated-NInfer-NVFP4 quantized NVFP4 — — apache-2.0 lyf 19 15.3k
ArtomYuan/Qwen3.8-27B-abliterated-ROCmFPX quantized GGUF — — apache-2.0 ArtomYuan 3 13.1k
edp1096/Huihui-RadixArk-Qwen3.8-27B-abliterated-NVFP4 quantized NVFP4 18.2B L — edp1096 1 11.2k
gearwave00001/Huihui-Qwen3.8-27B-abliterated-nvfp4-NInfer finetune nvfp4 — — apache-2.0 gearwave00001 2 9.9k
munekazu/Huihui-Qwen3.8-27B-abliterated-FP8 quantized -FP8 27.8B L apache-2.0 munekazu 3 9.8k
lyf/Qwen3.8-27B-Huihui-Abliterated-NVFP4-MTP-VL quantized NVFP4 27.8B L apache-2.0 lyf 3 8.8k
dongfangshuo/Dongfangshuo-Qwen3.8-27B-NSFW finetune — 27.8B L apache-2.0 dongfangshuo 10 7.8k
mitkox/Huihui-Qwen3.8-27B-abliterated-Q4_K_M-GGUF quantized GGUF — — apache-2.0 mitkox 6 7.5k
AutisticAF/Huihui-Qwen3.8-27B-abliterated-mlx-4Bit quantized mlx 26.9B L apache-2.0 AutisticAF 9 7.1k
renketong/Huihui-Qwen3.8-27B-abliterated-NVFP4-GGUF quantized NVFP4 — — apache-2.0 renketong 1 7.1k
lued/Qwen3.8-27B-huihui-abliterated-INT8-W8A16-MTP quantized INT8 27.8B L apache-2.0 lued 4 6.9k
donghanasd/Huihui-Qwen3.8-27B-abliterated-KO-Ridge-3.7bpw-GGUF quantized 7bpw — — apache-2.0 donghanasd 6 5.2k
IsValorum/Huihui-Qwen3.8-27B-Abliterated-VAL-APEX-I-NanoPlus-V3-GGUF quantized GGUF — — apache-2.0 IsValorum 5 5.2k
IsValorum/Huihui-Qwen3.8-27B-Abliterated-VAL-APEX-I-MiniPlus-V3-GGUF quantized GGUF — — apache-2.0 IsValorum 3 4.7k
ajaeger74/Huihui-Qwen3.8-27B-abliterated-Q6_K-GGUF quantized Q6_K — — apache-2.0 ajaeger74 2 4.4k
KostkaIT/Qwen3.8-27B-Huihui-Abliterated-oQ6e-MTP-MLX quantized MLX 27.8B L apache-2.0 KostkaIT 6 3.9k
leoncca/Qwen3.8-27B-Huihui-AWQ quantized AWQ 27.8B L apache-2.0 leoncca 1 4.1k
ailexleon/Huihui-Qwen3.8-27B-abliterated-mlx-4Bit quantized mlx 27.4B L apache-2.0 ailexleon 1 3.7k
leoncca/Qwen3.8-27B-Huihui-Mixed-FP8 quantized -FP8 27.8B L apache-2.0 leoncca 1 3.5k
KostkaIT/Qwen3.8-27B-Huihui-Abliterated-oQ4e-MTP-MLX quantized MLX 27.8B L apache-2.0 KostkaIT 4 3.3k
ailexleon/Huihui-Qwen3.8-27B-abliterated-mlx-6Bit quantized mlx 27.4B L apache-2.0 ailexleon 1 3.2k
batsclamp/Huihui-Qwen3.8-27B-abliterated-FP8-v2 quantized -FP8 27.4B L apache-2.0 batsclamp 0 3.1k
ailexleon/Huihui-Qwen3.8-27B-abliterated-mlx-8Bit quantized mlx 27.4B L apache-2.0 ailexleon 1 2.9k
ababaka/Huihui-Qwen3.8-27B-Abliterated-W4A16-AutoRound quantized -W4A16 6.26B M apache-2.0 ababaka 3 2.7k
Guile/Qwen3.8-27B-Humanlike-Chat-GGUF quantized GGUF — — apache-2.0 Guile 6 2.5k
trailio/Huihui-Qwen3.8-27B-abliterated-NVFP8 quantized — 27.8B L apache-2.0 trailio 0 2.5k
augustine223/Huihui-Qwen3.8-27B-abliterated-KO-i1-GGUF quantized GGUF — — apache-2.0 augustine223 1 2.4k
dongfangshuo/Dongfangshuo-Qwen3.8-27B-NSFW-v4 finetune GGUF 26.9B L other dongfangshuo 6 2.1k
satellitedown/Huihui-Qwen3.8-27B-abliterated-NVFP4-NInfer-v3 quantized NVFP4 — — apache-2.0 satellitedown 1 2.3k
Yirasumi/Huihui-Qwen3.8-27B-abliterated-INT4-W4A16 quantized INT4 5.16B M apache-2.0 Yirasumi 0 2.1k

Repository changelog

1 change
changed in the last 7 daysOther: 2026-10-24all changes

All providers

1 provider · 1 endpoint

Where to run 1 providers · 1 endpoints

Hosted endpoints observed for Huihui-Qwen3.8-27B-abliterated, sorted by input price (USD per million tokens). Each row names its observer and date; prices change daily, so check the source before quoting.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
Featherless
hf
huihui-ai/Huihui-Qwen3.8-27B-abliterated — — — — — — — live 2026-10-25

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  • Qwen3.8-27B · 27.8B
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  • Qwen3.6-27B · 27.8B
    same size band (L), same task (image-text-to-text), more providers, permissive license
  • Qwen3.5-27B · 27.8B
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Sources

3 sources

Sources

Hub snapshot: 2026-10-25 · Providers: 2026-10-24 21:44 UTC · Articles: 2026-10-24 21:46 UTC · Summary: 2026-10-09 02:04 UTC · Last verified 2026-10-25

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