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.
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.64preserved 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.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q4_K_M.gguf | Weights | 17.3 GB | f3421e9dbd57 |
| ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q5_K_M.gguf | Weights | 20.2 GB | 981db99efaaf |
| ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q6_K.gguf | Weights | 22.4 GB | e6398784f7d5 |
| ATX-Swift-1.5-Qwen3.8-27B-Uncensored-MTP-i1-Q8_0.gguf | Weights | 29.0 GB | 6ae762c99a27 |
| mmproj-BF16.gguf | Weights | 931.1 MB | 19acd7fcf4ee |
| README.md | Documentation | 3.5 KB | — |
| imatrix_atx_uncensored.dat | Other | 13.6 MB | 2e6d1d10274c |
| .gitattributes | Repository | 2.0 KB | — |
License and Download
- License
- apache-2.0
- Access
- Open weights, no gate
- Download size
- 89.9 GB
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
| Precision | Weights in memory |
|---|---|
| As published | 89.9 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.