Model overview
Community **conversion and component combination**, **not a newly trained model**. The NInfer v3 artifact combines the Huihui *abliterated Swift-1.5 GSQ-RCO IQ3_S* GGUF text weights (including MTP), a pretrained Qwen3.8-27B DFlash2 drafter, and the Qwen3.8-27B vision projector. > **RTX 4090 local benchmark (19 October 2026): up to 229.04 output tokens/s in a 2,048-token single-request decode test (32K input), 191.78 tokens/s at 160K input, and 63/63 successful HTTP requests.** These are *client-side measurements of the entire server*, not isolated DFlash2 speedups. See BENCHMARK.md for methodology and limits. This file is **not** a standard Transformers checkpoint and cannot be loaded directly with `transformers.AutoModel.from_pretrained`.
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。