Model overview
GGUF quantizations of **empero-ai/Qwythos-9B-v2** for llama.cpp, Ollama, LM Studio, jan, KoboldCpp, and other GGUF runtimes. **Qwythos-9B-v2 is the new and improved Qwythos** — all the deep chain-of-thought reasoning of the base Qwythos, with the **looping behavior fixed**. The looping/degeneration that showed up under greedy or low-temperature decoding is trained out (**6.7% → 0%**), the native **MTP head is restored**, and the identity prompt is cleaned up — while knowledge and reasoning are held at (or above) the base Qwythos level. The fix uses **FTPO (Final-Token Preference Optimization)**: the exact token that *starts* a repetition loop is identified and the model is gently trained to prefer coherent alternatives at that one position, leaving the rest of the distribution — and therefore its knowledge and reasoning — untouched.
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：apache-2.0。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。