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AI 模型库/WaveCut/Qwen3.8-Flash-Next-GSQ-RCO-Q2_0-NInfer-v3
MODEL PROFILE · 模型档案

Qwen3.8-Flash-Next-GSQ-RCO-Q2_0-NInfer-v3

WaveCut · Qwen3.8-Flash-Next-GSQ-RCO-Q2_0-NInfer-v3

A NInfer **v3** artifact of ISTA-DASLab's Qwen3.8-Flash-Next GSQ-RCO Q2_0 (2.40 bits per weight over the transformer weights) for **NInfer-all**, the `master` branch of iamwavecut/ninfer-all. Qwen3.8-Flash-Next is a 125B-parameter mixture of experts: 48 layers of 512 routed experts, 10 of them active per token, about 6B active parameters. The GGUF assigns a ggml quantization type to every tensor; this artifact keeps each tensor's ggml blocks byte for byte (the hyper-connection projections excepted: they are re-quantized from BF16 to Q8_0), and the engine multiplies the blocks in place. Q2_0 is the release built for speed: it avoids the lookup-table formats. Stock NInfer builds refuse these files: the model family and the `gguf_*` formats exist only in that line; build `master` from commit `5395ec30b` on. NInfer serves it with up to eight concurrent requests, prompt-prefix reuse, structured output and its Vision tower; This file includes the MTP block. Enable drafting with `--spec mtp --draft-tokens 4`. One file, `Qwen3.8-Flash-Next-GSQ-RCO-Q2_0-ninfer-v3.ninfer`, of 40,709,159,936 bytes (37.91 GiB), next to its conversion report, `SHA256SUMS`, `NOTICE` and `LICENSE`. Original text/Vision conversion command, before the MTP attachment:

译文排队中，当前展示来源原文。

视觉问答license:other
上下文窗口来源未披露
输入 → 输出文本、图像 → 文本
模型权重待核验
档案更新时间2026/11/2 19:17:09
OVERVIEW

模型介绍

A NInfer **v3** artifact of ISTA-DASLab's Qwen3.8-Flash-Next GSQ-RCO Q2_0 (2.40 bits per weight over the transformer weights) for **NInfer-all**, the `master` branch of iamwavecut/ninfer-all. Qwen3.8-Flash-Next is a 125B-parameter mixture of experts: 48 layers of 512 routed experts, 10 of them active per token, about 6B active parameters. The GGUF assigns a ggml quantization type to every tensor; this artifact keeps each tensor's ggml blocks byte for byte (the hyper-connection projections excepted: they are re-quantized from BF16 to Q8_0), and the engine multiplies the blocks in place. Q2_0 is the release built for speed: it avoids the lookup-table formats. Stock NInfer builds refuse these files: the model family and the `gguf_*` formats exist only in that line; build `master` from commit `5395ec30b` on. NInfer serves it with up to eight concurrent requests, prompt-prefix reuse, structured output and its Vision tower; This file includes the MTP block. Enable drafting with `--spec mtp --draft-tokens 4`. One file, `Qwen3.8-Flash-Next-GSQ-RCO-Q2_0-ninfer-v3.ninfer`, of 40,709,159,936 bytes (37.91 GiB), next to its conversion report, `SHA256SUMS`, `NOTICE` and `LICENSE`. Original text/Vision conversion command, before the MTP attachment:

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价，请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

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。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用？

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗？

不是实时结算价格，而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

huggingface · WaveCut/Qwen3.8-Flash-Next-GSQ-RCO-Q2_0-NInfer-v3 ↗2026/10/29 20:06:27
huggingface · enrich:cb990fef-75cf-42ec-bcc5-52a9c33fe0ff ↗2026/10/30 08:33:56

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。