Model overview
Recently re-quantized with the latest version of advanced-gguf-quantizer tool. MTP included. This latest (6-June-2026) NVFP4 quant of Qwen3.6-27B keeps quality very high, while improving KLD, tail KLD metrics, top-token stability, and probability error compared to the earlier releases. It is faster and smaller in size. It applies my RSF scale fitting technique to the Q_K quants and uses a different tensor mix layout compared to previously. 6-June-2026: changed the MTP tensors to be NVFP4, ~130tk/s tg is now possible in some configurations on 5090. I am experimenting with a smaller verison of this model designed to be used on machines with 16GB of VRAM: Qwen3.6-27B-NVFP4-SMALL-MTP-GGUF . The SMALL version will be slower than this model but should maintain similar quality, although I am still evaluating it.
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。