Can I run this LLM? Real file sizes, live from Hugging Face.
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Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP requirements — can you run it?

· 10 quantizations measured · updated 2026-09-19 · source: DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP-GGUF

Every quantization: real file size vs what you actually need

QuantFile (measured)VRAM/RAM needed (8K ctx)Runs on (first fit)
IQ2_M12.1 GB16.0 GBRTX 3090 24GB
Q4_K_S17.5 GB22.5 GBRTX 5090 32GB
IQ4_NL17.8 GB22.8 GBRTX 5090 32GB
Q5_K_S20.6 GB26.3 GBRTX 5090 32GB
Q5_K_M21.2 GB26.9 GBRTX 5090 32GB
IQ3_M28.6 GB35.8 GBRTX PRO 6000 96GB
Q4_K_M36.5 GB45.4 GBRTX PRO 6000 96GB
IQ4_XS48.9 GB60.2 GBRTX PRO 6000 96GB
Q8_060.0 GB73.5 GBRTX PRO 6000 96GB
Q6_K70.0 GB85.6 GBRTX PRO 6000 96GB

KV cache uses a flat +20% context/overhead rule because this repo does not publish its config; exact numbers may differ for long contexts. MoE models keep all experts in memory — total size counts, not just active params.

Can I run Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP on my GPU? (IQ2_M recommended quant)

HardwareMemoryVerdict
RTX 3060 12GB12 GBno
RTX 4060 Ti 16GB16 GBno
RTX 3090 24GB24 GBRUNS
RTX 4090 24GB24 GBRUNS
RTX 5090 32GB32 GBRUNS
RTX PRO 6000 96GB96 GBRUNS
Mac 16GB unified16 GBno
Mac 32GB unified32 GBRUNS
Mac 64GB unified64 GBRUNS
Mac 128GB unified128 GBRUNS
Mac 256GB unified256 GBRUNS
Mac 512GB unified512 GBRUNS
32GB system RAM (CPU)32 GBRUNS
64GB system RAM (CPU)64 GBRUNS
128GB system RAM (CPU)128 GBRUNS
256GB system RAM (CPU)256 GBRUNS
1TB server RAM (CPU)1024 GBRUNS
2TB server RAM (CPU)2048 GBRUNS

How much VRAM does Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP need?

The honest answer: 16.0 GB at the IQ2_M quant with 8K context — that is the measured file size (12.1 GB) plus KV cache and runtime overhead. The smallest published build needs 16.0 GB; the lossless one needs 85.6 GB.

Can I run it with CPU offload?

Yes, if combined RAM+VRAM ≥ file size — but generation speed is limited by memory bandwidth. Expect roughly: DDR5 dual channel ~10-30 tok/s for small MoE actives, single digits for big ones, 0.1-1 tok/s when experts page from disk. CPU-only is fine for batch jobs, painful for chat.

Why do other sites show different numbers?

Most pages compute weights from a formula (params × bits/8). We use the actual file sizes published in GGUF repos, which include the embedding table, unquantized tensors, and container overhead — that is why our numbers can differ from a naive calculation.

FAQ

How much VRAM does Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP need?

The measured answer: 16.0 GB at the IQ2_M quant with 8K context. The smallest published build needs 16.0 GB; the lossless (F16/BF16) build needs 85.6 GB. These are real GGUF file sizes from Hugging Face, not formula estimates.

Can I run Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP on a 24GB GPU (RTX 3090/4090)?

Yes — at IQ2_M (16.0 GB). Quants that fit 24GB: IQ2_M, Q4_K_S, IQ4_NL.

Can I run Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP on CPU with system RAM?

Yes, if your usable RAM is at least the file size. At IQ2_M you need ~16.0 GB of RAM. CPU generation is memory-bandwidth-bound: expect single-digit tok/s for large MoE models, 10-30 tok/s for small active params, and below 1 tok/s when experts page from disk.

Why do VRAM numbers for Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP differ between sites?

Most sites compute weights from a formula (params x bits/8). ModelFit uses the actual GGUF file sizes published on Hugging Face, which include the embedding table, unquantized tensors, and container overhead — so our numbers reflect what you really download and load.

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