MODEL PROFILE · 模型档案

Qwen3.8-Flash-CIRU-STRIX-Orca

jcbtc · Qwen3.8-Flash-CIRU-STRIX-Orca

OrcaRouter's Qwen3.8 Flash research checkpoint, converted to a compact expert format for AMD Strix Halo and the native CIRU v5 runtime. **The original Orca version remains available through its existing download parts and assembly helper.** The v5.0 GGUF is an additional, versioned choice. Both versions use Orca's matching Q8 multi-token prediction (MTP) draft, the required paged token-embedding files, and the matching Orca vision projector. > [!IMPORTANT] > The compact expert format needs the matching CIRU runtime. Stock llama.cpp > and Hugging Face hosted inference do not load it. Keep the required `ple/` > token-embedding files on fast local storage. Runtime **v5.5.0** retains the v5 model and runtime features, adding the corrected concurrent MTP/attention paths and post-image memory-pressure fix. The existing v5.0 weights are unchanged. The default remains **one slot, 262,144 context tokens, MTP4**, with a 16,384-token batch and an **8,192-token microbatch**.

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 19:15:39
OVERVIEW

模型介绍

OrcaRouter's Qwen3.8 Flash research checkpoint, converted to a compact expert format for AMD Strix Halo and the native CIRU v5 runtime. **The original Orca version remains available through its existing download parts and assembly helper.** The v5.0 GGUF is an additional, versioned choice. Both versions use Orca's matching Q8 multi-token prediction (MTP) draft, the required paged token-embedding files, and the matching Orca vision projector. > [!IMPORTANT] > The compact expert format needs the matching CIRU runtime. Stock llama.cpp > and Hugging Face hosted inference do not load it. Keep the required `ple/` > token-embedding files on fast local storage. Runtime **v5.5.0** retains the v5 model and runtime features, adding the corrected concurrent MTP/attention paths and post-image memory-pressure fix. The existing v5.0 weights are unchanged. The default remains **one slot, 262,144 context tokens, MTP4**, with a 16,384-token batch and an **8,192-token microbatch**.

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

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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

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。