Model overview
A standalone, **weight-baked uncensored & abliterated GGUF** of **`ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF`.** This build is created by precisely transplanting 144 orthogonalized residual-writing tensors from **`orcarouter/Qwen3.8-Flash-Next-Uncensored`** (via `SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF`) directly into the optimized 256-expert pruned Coder architecture. `ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF` compresses `Qwen3.8-Flash-Next` from 354 GB (BF16, 512 experts per layer) down to **58.4 GB** by combining: 1. **Structured Expert Pruning ($512 \rightarrow 256$ experts per layer):** Selects the 256 experts specialized for software engineering, coding, agentic tool calling, and vision. 2. **GSQ (Gumbel-Softmax Quantization) + RCO (Riemannian Co-design Search):** Assigns optimal mixed-precision GGUF quantization types across individual tensors while storing the retained weights at `~3.5 bits` (`IQ3_S`-equivalent fidelity, labeled `IQ1_M` for its `1.89` effective bits per parameter relative to the unpruned 512-expert model). --- Because this is an ultra-low-bit MoE model (`IQ1_M` effective / `IQ3_S` retained weights), **avoid pure greedy decoding (`--temp 0.0` with no repetition penalty)** on repetitive C/C++ struct definitions. Use standard Qwen sampling parameters with a light repetition/presence penalty:
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：来源未披露，须进一步核验。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。