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Open-weight model

ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-GGUF

by Alejandro Melo bjivanovich/ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-GGUF

ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-GGUF is an open-weight model from Alejandro Melo, released under Apache License 2.0. Its published files total 89.9 GB. It draws 91 downloads a month.

Custom ATX GGUF quantizations of Swift-1.5-Qwen3.8-27B-Uncensored-MTP featuring an embedded Multi-Token Prediction (MTP) draft head in blk.64, specifically optimized for high-throughput inference in llamAmpere and standard llama.cpp.

Parameters—
Context—
Weights89.9 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads91

Model Card

By Alejandro Melo, published under apache-2.0, revision 0db409a66811.

Custom ATX GGUF quantizations of Swift-1.5-Qwen3.8-27B-Uncensored-MTP featuring an embedded Multi-Token Prediction (MTP) draft head in blk.64, specifically optimized for high-throughput inference in llamAmpere and standard llama.cpp. While compatible with upstream llama.cpp, this model family is engineered for llamAmpere, a specialized high-performance fork tuned for NVIDIA Ampere (SM86) and Ada Lovelace architectures (RTX 3090 / RTX 4090). - MMA Fused Q8 Kernels (GGMLQ8TURBO3MMAFUSED="1"): Eliminates memory bandwidth bottlenecks and achieves peak Tensor Core utilization. - Hardware-Accelerated MTP Decoding (--spec-type draft-mtp): Reaches 45-60+ tokens/s on a single RTX 3090 (24GB) via…

Read Alejandro Melo's full model card

Custom ATX GGUF quantizations of Swift-1.5-Qwen3.8-27B-Uncensored-MTP featuring an embedded Multi-Token Prediction (MTP) draft head in blk.64, specifically optimized for high-throughput inference in llamAmpere and standard llama.cpp.


Optimized Engine: llamAmpere

While compatible with upstream llama.cpp, this model family is engineered for llamAmpere, a specialized high-performance fork tuned for NVIDIA Ampere (SM86) and Ada Lovelace architectures (RTX 3090 / RTX 4090).

Key Features Enabled in llamAmpere:

  • MMA Fused Q8 Kernels (GGML_Q8_TURBO3_MMA_FUSED="1"): Eliminates memory bandwidth bottlenecks and achieves peak Tensor Core utilization.
  • Hardware-Accelerated MTP Decoding (--spec-type draft-mtp): Reaches 45-60+ tokens/s on a single RTX 3090 (24GB) via self-speculative draft verification.
  • Turbo3 Quantized KV Cache (-ctk q8_0 -ctv turbo3): Unlocks 131k+ context lengths inside 24GB VRAM with zero context truncation.
  • Zero Warp Divergence: Non-linear quants (IQ4_NL, IQ3_S) are omitted in favor of linear K-quants (Q5_K_M, Q6_K, Q8_0) to guarantee deterministic CUDA execution.

Model Lineage & Architecture

  • Uncensored (Abliterated): Refusal directions neutralised across 131 core tensors (attention projections, MLP down-projections, and token embeddings).
  • Swift 1.5 Architecture: Generates 58.5% fewer internal thinking tokens compared to base Qwen 2.5/3.0 models for 2x faster response delivery.
  • Embedded MTP Head: 15 draft tensors located in blk.64 preserved at high precision (Q8_0) for speculative decoding draft acceptance rates above 80%.
  • Custom imatrix Calibration (i1): Calibrated against technical reasoning, code generation, and multi-turn conversational corpora.

Available Model Files

File Size Target Hardware Description
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q8_0.gguf ~29.0 GiB 48 GB VRAM / Dual GPU Near-lossless master precision.
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q6_K.gguf ~22.4 GiB 32 GB VRAM High-fidelity quantization.
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q5_K_M.gguf ~20.2 GiB 24 GB VRAM (RTX 3090/4090) Recommended Sweet Spot for llamAmpere.
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q4_K_M.gguf ~16.8 GiB 20-24 GB VRAM Fast and lightweight.

Recommended Execution (llamAmpere on Windows PowerShell)

Clone and build the repository from GitHub: JakeATX/llamAmpere, then run:

```powershell $env:GGML_Q8_TURBO3_MMA_FUSED="1"

.uild-sm86in\llama-server.exe -m "ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q5_K_M.gguf" -ngl 99 -c 131072 -b 4096 -ub 512 -fa on -ctk q8_0 -ctv turbo3 --spec-type draft-mtp --spec-draft-n-max 3 --spec-draft-p-min 0 --spec-draft-type-k q8_0 --spec-draft-type-v q8_0 --spec-draft-vocab-map "D:\llamAmpere\docs\mtp-vocab\atx_65536.txt" --temp 0.6 --top-p 0.95

Upstream References Original Architecture & Uncensoring: ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-MTP Inference Engine: JakeATX/llamAmpere

Identity and Version

Repository
bjivanovich/ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-GGUF
Publisher
Alejandro Melo
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
Not stated by the source
Languages
atx, mtp
Revision
0db409a66811ea80acba8c49fbaaa36ea21d118f
First published
2026-09-28
Last updated
2026-09-30

Files and Weights

8 files, 89.9 GB in total. The weights are 5 files totalling 89.9 GB in gguf.

Weights5 files · 89.9 GB
Documentation1 file · 3.5 KB
Other1 file · 13.6 MB
Repository1 file · 2.0 KB
Every file
FileTypeSizeSHA-256
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q4_K_M.ggufWeights17.3 GB f3421e9dbd57
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q5_K_M.ggufWeights20.2 GB 981db99efaaf
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q6_K.ggufWeights22.4 GB e6398784f7d5
ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q8_0.ggufWeights29.0 GB 6ae762c99a27
mmproj-BF16.ggufWeights931.1 MB 19acd7fcf4ee
README.mdDocumentation3.5 KB —
imatrix_atx_uncensored.datOther13.6 MB 2e6d1d10274c
.gitattributesRepository2.0 KB —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
89.9 GB
Download from Alejandro Melo

Released by Alejandro Melo through its official repository on Hugging Face. Read the license.

Built From

  • Derived from ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-MTP
  • Quantized from ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-MTP

Memory Requirements

PrecisionWeights in memory
As published89.9 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-GGUF

Can I use ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-GGUF commercially?

Yes. ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-GGUF is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.