How much VRAM does OFFELLIA_Quantis need?

Q4_K_M is exactly 76,480,954,528 bytes (71.23 GiB) in weights. Add the KV cache, which depends on context length, plus roughly half a gigabyte of runtime overhead.

Brunobkr · text

OFFELLIA_Quantis

Brunobkr/OFFELLIA_Quantis

OFFELLIA_Quantis at Q4_K_M is exactly 76,480,954,528 bytes (71.23 GiB / 76.48 GB)

From the file· summed from 10 file(s)

Parameters

7.6B

Architecture

qwen2vl

Context

—

native (config.json)

License

mit

Shipped quantizations

● exact bytes, summed from published files

Quant	Size●	Exact bytes●	Effective bpw●	Tensors●	Publisher
Q4_K	4.70 GiB	5,044,779,712	5.299	—	Brunobkr
F16	14.97 GiB	16,068,895,872	16.880	—	Brunobkr
Q8_06 shards	31.57 GiB	33,896,029,312	—	—	Brunobkr
Q4_K_M10 shards	71.23 GiB	76,480,954,528	—	—	Brunobkr

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 Q4_K_M at roughly 3.99 GiB. The real file is 71.23 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 OFFELLIA_Quantis need?: Q4_K_M is exactly 76,480,954,528 bytes (71.23 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of OFFELLIA_Quantis 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.