Model overview
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.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。