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ISTA-DASLab's IQ1_M Coder GGUF of Qwen3.8-Flash-Next (ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF at 5348543e) with 768 of its 12,288 routed experts removed, served through MLX as an OpenAI-compatible endpoint for coding agents. Each layer keeps 185 to 255 of 256 routed experts, 240 on average; kept tensors are byte for byte as published. This repository is the model folder and its runner in one; the runtime is a TensorFold fork that reads the GGUF tensors in place through mlx-kquant. The fork builds on TensorFold 0.3.4 (MIT) and carries its Python engine, which upstream later replaced with a native one. `DRAFTING=off ./serve.sh` turns drafting off and keeps the disconnect and title behaviour. Some `evidence/` pages were measured with drafting off and without the disconnect and title behaviour; each says which. Requires an Apple Silicon Mac with 48 GB (for 24 GB and 32 GB Macs, see below) and macOS 26 or later (measured on an M4 Pro), about 62 GB of free disk (57 GB model files, 2.2 GB head, about 1 GB environment), git and uv (the download below uses `uvx`; `install.sh` also works with python3.11). Close memory-heavy apps first: `serve.sh` will not start if macOS reports memory pressure or has less than an estimated 36 GB free or held by cached files. This is a startup check; it does not guarantee that memory will suffice later.

Text generation
Input Text→ Output Text
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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Category pending
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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Basic profile indexed · More details to follow

Category pending
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗
Source / docs ↗
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