Arki05/Qwen3.8-27B-GGUF-shards overview
Qwen3.8 27B — per type GGUF store qalloc store v2 This repo is a byte addressable quantization store , not a single quant. It holds Qwen3.8 27B quantized at ~4…
Runs locally from ~13.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| calib/imatrix/qwen38_code.imatrix.gguf | GGUF | GGUF | 13.0 MB | Download |
| calib/imatrix/qwen38_encode_basis.imatrix.gguf | GGUF | GGUF | 13.0 MB | Download |
| calib/imatrix/qwen38_finemath.imatrix.gguf | GGUF | GGUF | 13.0 MB | Download |
| calib/imatrix/qwen38_fineweb-edu.imatrix.gguf | GGUF | GGUF | 13.0 MB | Download |
| calib/imatrix/qwen38_general-instruct.imatrix.gguf | GGUF | GGUF | 13.0 MB | Download |
| calib/imatrix/qwen38_nemotron-agentic.imatrix.gguf | GGUF | GGUF | 13.0 MB | Download |
| calib/imatrix/qwen38_reasoning.imatrix.gguf | GGUF | GGUF | 13.0 MB | Download |
| equivalents/UD-IQ1_M.gguf | GGUF | IQ1_M | 6.27 GB | Download |
| equivalents/UD-IQ1_S.gguf | GGUF | IQ1_S | 5.77 GB | Download |
| equivalents/UD-IQ2_S.gguf | GGUF | IQ2_S | 7.80 GB | Download |
| equivalents/UD-IQ2_XXS.gguf | GGUF | IQ2_XXS | 6.77 GB | Download |
| equivalents/UD-IQ3_S.gguf | GGUF | IQ3_S | 10.89 GB | Download |
| equivalents/UD-IQ3_XXS.gguf | GGUF | IQ3_XXS | 9.86 GB | Download |
| equivalents/UD-IQ4_XS.gguf | GGUF | IQ4_XS | 12.95 GB | Download |
| equivalents/UD-Q2_K_XL.gguf | GGUF | Q2_K_XL | 8.83 GB | Download |
| equivalents/UD-Q3_K_XL.gguf | GGUF | Q3_K_XL | 11.92 GB | Download |
| equivalents/UD-Q4_K_M.gguf | GGUF | Q4_K_M | 15.01 GB | Download |
| equivalents/UD-Q4_K_S.gguf | GGUF | Q4_K_S | 13.98 GB | Download |
| equivalents/UD-Q4_K_XL.gguf | GGUF | Q4_K_XL | 16.03 GB | Download |
| equivalents/UD-Q5_K_M.gguf | GGUF | Q5_K_M | 18.09 GB | Download |
| equivalents/UD-Q5_K_S.gguf | GGUF | Q5_K_S | 17.06 GB | Download |
| equivalents/UD-Q5_K_XL.gguf | GGUF | Q5_K_XL | 19.12 GB | Download |
| equivalents/UD-Q6_K.gguf | GGUF | Q6_K | 20.15 GB | Download |
| equivalents/UD-Q6_K_L.gguf | GGUF | Q6_K_L | 22.20 GB | Download |
| equivalents/UD-Q6_K_M.gguf | GGUF | Q6_K_M | 21.17 GB | Download |
| equivalents/UD-Q6_K_XL.gguf | GGUF | Q6_K_XL | 23.23 GB | Download |
| equivalents/UD-Q8_K_L.gguf | GGUF | Q8_K_L | 25.79 GB | Download |
| main.gguf | GGUF | GGUF | 20.6 MB | Download |
| types/IQ1_BN.gguf | GGUF | GGUF | 5.19 GB | Download |
| types/IQ1_KT.gguf | GGUF | GGUF | 7.92 GB | Download |
| types/IQ1_M.gguf | GGUF | GGUF | 7.91 GB | Download |
| types/IQ1_S.gguf | GGUF | GGUF | 7.38 GB | Download |
| types/IQ2_BN.gguf | GGUF | GGUF | 6.39 GB | Download |
| types/IQ2_K.gguf | GGUF | GGUF | 7.56 GB | Download |
| types/IQ2_KL.gguf | GGUF | GGUF | 8.57 GB | Download |
| types/IQ2_KS.gguf | GGUF | GGUF | 6.98 GB | Download |
| types/IQ2_KT.gguf | GGUF | GGUF | 8.99 GB | Download |
| types/IQ2_S.gguf | GGUF | GGUF | 10.21 GB | Download |
| types/IQ2_XS.gguf | GGUF | GGUF | 9.50 GB | Download |
| types/IQ2_XXS.gguf | GGUF | GGUF | 8.79 GB | Download |
| types/IQ3_K.gguf | GGUF | GGUF | 10.94 GB | Download |
| types/IQ3_KS.gguf | GGUF | GGUF | 10.16 GB | Download |
| types/IQ3_KT.gguf | GGUF | GGUF | 9.97 GB | Download |
| types/IQ3_S.gguf | GGUF | GGUF | 10.94 GB | Download |
| types/IQ3_XXS.gguf | GGUF | GGUF | 9.75 GB | Download |
| types/IQ4_K.gguf | GGUF | GGUF | 14.32 GB | Download |
| types/IQ4_KS.gguf | GGUF | GGUF | 13.54 GB | Download |
| types/IQ4_KSS.gguf | GGUF | GGUF | 12.75 GB | Download |
| types/IQ4_KT.gguf | GGUF | GGUF | 12.75 GB | Download |
| types/IQ4_NL.gguf | GGUF | GGUF | 14.32 GB | Download |
| types/IQ4_XS.gguf | GGUF | GGUF | 13.53 GB | Download |
| types/IQ5_K.gguf | GGUF | GGUF | 17.50 GB | Download |
| types/IQ5_KS.gguf | GGUF | GGUF | 16.72 GB | Download |
| types/IQ6_K.gguf | GGUF | GGUF | 21.08 GB | Download |
| types/MXFP4.gguf | GGUF | GGUF | 13.53 GB | Download |
| types/NVFP4.gguf | GGUF | GGUF | 14.32 GB | Download |
| types/Q2_K.gguf | GGUF | GGUF | 8.36 GB | Download |
| types/Q3_K.gguf | GGUF | GGUF | 10.94 GB | Download |
| types/Q4_0.gguf | GGUF | GGUF | 14.32 GB | Download |
| types/Q4_1.gguf | GGUF | GGUF | 15.91 GB | Download |
| types/Q4_K.gguf | GGUF | GGUF | 14.32 GB | Download |
| types/Q5_0.gguf | GGUF | GGUF | 17.50 GB | Download |
| types/Q5_1.gguf | GGUF | GGUF | 19.09 GB | Download |
| types/Q5_K.gguf | GGUF | GGUF | 17.50 GB | Download |
| types/Q6_0.gguf | GGUF | GGUF | 20.68 GB | Download |
| types/Q6_K.gguf | GGUF | GGUF | 20.88 GB | Download |
| types/Q8_0.gguf | GGUF | GGUF | 27.04 GB | Download |
| types/TQ1_0.gguf | GGUF | GGUF | 5.38 GB | Download |
| types/TQ2_0.gguf | GGUF | GGUF | 6.57 GB | Download |
Model Details
Model README
---
license: apache-2.0
base_model: Qwen/Qwen3.8-27B
tags:
- gguf
- quantization
---
Qwen3.8-27B — per-type GGUF store (qalloc store-v2)
This repo is a byte-addressable quantization store, not a single quant.
It holds Qwen3.8-27B quantized at ~41 different types (mainline llama.cpp
and ik_llama.cpp families unified; per-type backend flag in the manifest):
types/<TYPE>.gguf— the whole model at one type. Every file is a normal,
directly runnable uniform quant (a mainline-typed file runs on stock
llama.cpp; ik types need ik_llama.cpp).
main.gguf— header KV metadata + all non-quantizable tensors (with the
upstream chat-template fix applied).
manifest.json(qalloc-manifest/v2) — the byte index: for every tensor
× type, the exact [offset, offset+bytes) range inside its per-type file.
A client can assemble any mixed-precision allocation with plain HTTP
Range requests — no server-side work.
calib/,eval/— the calibration and evaluation corpus files used by
the damage-model program that drives allocation.
Assembly tooling and the allocation picker (exact MCKP solver over a
measured damage model) live in the qalloc project; the interactive picker
runs in the browser via WASM. The former v1 stores (per-tensor files, two
repos) are deprecated: this repo IS the store.
Run Arki05/Qwen3.8-27B-GGUF-shards with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models