MODEL PROFILE

Qwen3.8-27B-NVIDIA-NVFP4-NInferV3

wallawalla47 · Qwen3.8-27B-NVIDIA-NVFP4-NInferV3

**A single-file NInfer V3 (`.ninfer`) artifact of nvidia/Qwen3.8-27B-NVFP4, built for an NVIDIA RTX 5090 (sm_120a), for Infernix (recommended) and NInfer. No conversion step at load time: point `infernix-serve` (or `ninfer-serve`) at the `.ninfer` file and run.** This repository is the NInfer form of the NVIDIA checkpoint above: the Model Optimizer mixed NVFP4/FP8 weights are carried over **bit-exactly** for every transformer linear except the language-model head, and two speculative-decoding components (DFlash2 draft model, indexed proposal head) are added so the artifact runs with the engines' fastest decode paths. **Recommended engine: Infernix**, my engine grown from NInfer, which replaces my earlier ninfer-custom fork. In an agentic coding replay on the 27B it served 90 % of prompt tokens from its prefix cache and reached the first token in about half NInfer's average time, and it prefills long prompts 1.3-1.5× faster, at the same quality (benchmarks, measured on NInfer's official 27B artifact). It also runs Qwen3.8-Flash-Next. The artifact still works with NInfer itself and with ninfer-custom.

Visual QAmultimodalreasoninglicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/11/2 19:15:52
OVERVIEW

Model overview

**A single-file NInfer V3 (`.ninfer`) artifact of nvidia/Qwen3.8-27B-NVFP4, built for an NVIDIA RTX 5090 (sm_120a), for Infernix (recommended) and NInfer. No conversion step at load time: point `infernix-serve` (or `ninfer-serve`) at the `.ninfer` file and run.** This repository is the NInfer form of the NVIDIA checkpoint above: the Model Optimizer mixed NVFP4/FP8 weights are carried over **bit-exactly** for every transformer linear except the language-model head, and two speculative-decoding components (DFlash2 draft model, indexed proposal head) are added so the artifact runs with the engines' fastest decode paths. **Recommended engine: Infernix**, my engine grown from NInfer, which replaces my earlier ninfer-custom fork. In an agentic coding replay on the 27B it served 90 % of prompt tokens from its prefix cache and reached the first token in about half NInfer's average time, and it prefills long prompts 1.3-1.5× faster, at the same quality (benchmarks, measured on NInfer's official 27B artifact). It also runs Qwen3.8-Flash-Next. The artifact still works with NInfer itself and with ninfer-custom.

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.

PRICING & COST

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INDEPENDENT BENCHMARKS

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。

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Frequently asked questions

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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。