Model overview
An INT4 AutoRound quantization of bottlecapai/ThinkingCap-Qwen3.8-27B, BottleCap AI's reasoning fine-tune of Qwen/Qwen3.8-27B. It is **19.0 GB** and keeps the **MTP head** for self-speculative decoding. BottleCap publishes FP8, NVFP4 and GGUF builds, but no INT4 AutoRound. This one exists so the model can run on two 24 GB cards with the same tiers as the base Qwen3.8-27B in club-3090. The packed layout is tensor-for-tensor identical to Frozenlock/Qwen3.8-27B-int4-AutoRound: the same quantized and BF16 module families, and the same MTP tensors. So it should load anywhere that checkpoint does. Only the tuning differs: 512 samples with alg_ext here, where that card says "default tuning".
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。