Model overview
Quantized GGUF of **Blackfrost-AI/CYBER-FROST-3.8-BF16** — a cybersecurity-tuned 3.8-generation Qwen4-Exp MoE — built by peasantsmith. This is a **biased-precision** quant: rather than applying one global bit-width, each tensor class is placed at the precision where it does the most good, guided by imatrix-weighted reconstruction error and a floor determined from the ISTA-DASLab reference quant. The routed experts and the n-gram table are 97% of the model between them — those two components are where any future size/quality trade-off would be made.
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。