BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF overview
BoneMangler/Qwen3 Coder 42B A3B Instruct TOTAL RECALL MASTER CODER M 512k ctx W4A16 Q8 0 GGUF This model was converted to GGUF format from tcclaviger/Qwen3 Cod…
Runs locally from ~41.98 GB disk (32 GB+ VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| qwen3-coder-42b-a3b-instruct-total-recall-master-coder-m-512k-ctx-w4a16-q8_0.gguf | GGUF | Q8_0 | 41.98 GB | Download |
Model Details
| Model ID | BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF |
|---|---|
| Author | BoneMangler |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | tcclaviger/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16 |
| Last modified | 2026-06-17T06:40:53.000Z |
Model README
---
license: apache-2.0
library_name: transformers
model_size: 42B
language:
- en
- fr
- zh
- de
tags:
- quantized
- gptq
- w4a16
- llm-compressor
- qwen3
- mixture-of-experts
- coding
- programming
- code generation
- code
- codeqwen
- moe
- coder
- qwen2
- chat
- qwen
- qwen-coder
- Qwen3-30B-A3B
- mixture of experts
- 128 experts
- 8 active experts
- 512k context
- finetune
- brainstorm 20x
- brainstorm
- optional thinking
- qwen3_moe
- rocm
- amd
- r9700
- RDNA4
- gfx1201
- ultra quality
- llama-cpp
- gguf-my-repo
base_model: tcclaviger/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16
pipeline_tag: text-generation
---
BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF
This model was converted to GGUF format from tcclaviger/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF --hf-file qwen3-coder-42b-a3b-instruct-total-recall-master-coder-m-512k-ctx-w4a16-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF --hf-file qwen3-coder-42b-a3b-instruct-total-recall-master-coder-m-512k-ctx-w4a16-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF --hf-file qwen3-coder-42b-a3b-instruct-total-recall-master-coder-m-512k-ctx-w4a16-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF --hf-file qwen3-coder-42b-a3b-instruct-total-recall-master-coder-m-512k-ctx-w4a16-q8_0.gguf -c 2048Run BoneMangler/Qwen3-Coder-42B-A3B-Instruct-TOTAL-RECALL-MASTER-CODER-M-512k-ctx-W4A16-Q8_0-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models