How much VRAM does qwen27b-abliterated-Fable-MTP need?

Q2_K is exactly 10,864,592,608 bytes (10.12 GiB) in weights. Add the KV cache, which depends on context length, plus roughly half a gigabyte of runtime overhead.

hotdogs · text

qwen27b-abliterated-Fable-MTP

hotdogs/qwen27b-abliterated-Fable-MTP

qwen27b-abliterated-Fable-MTP at Q2_K is exactly 10,864,592,608 bytes (10.12 GiB / 10.86 GB) — an effective 3.181 bits per weight, not the nominal 2.

From the file· summed from 1 file(s)

Parameters

27.3B

Architecture

qwen35

Context

—

native (config.json)

License

agpl-3.0

Shipped quantizations

● exact bytes, summed from published files

Quant	Size●	Exact bytes●	Effective bpw●	Tensors●	Publisher
Q2_K	10.12 GiB	10,864,592,608	3.181	—	hotdogs
IQ4_NL	14.90 GiB	15,998,539,680	4.685	—	hotdogs
Q6_K	20.89 GiB	22,430,998,688	6.568	—	hotdogs
F16	50.90 GiB	54,657,732,768	16.005	—	hotdogs

Compare with

same modality, comparable size

vs Qwen3-Coder-30B-A3B-Instruct vs Qwen3.6-27B vs Qwen3.8-27B vs gemma-4-12B-it-qat-q4_0-unquantized vs gemma-4-E4B-it vs Qwen3-30B-A3B-Thinking-2507 All alternatives →Will it fit on my card? →

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q2_K at roughly 14.31 GiB. The real file is 10.12 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

Architecture unavailable — this repository is gated and no ungated mirror was found. Exact file sizes above are still authoritative; only the KV math needs the config.

Questions people ask

How much VRAM does qwen27b-abliterated-Fable-MTP need?: Q2_K is exactly 10,864,592,608 bytes (10.12 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of qwen27b-abliterated-Fable-MTP should I use?: Q4_K_M is the usual default. Pick the largest quantization that fits your card at the context you actually need — the table above gives exact sizes for every one published.