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AI 模型库/AtomicChat/Nanbeige4.3-33B-GGUF
MODEL PROFILE · 模型档案

Nanbeige4.3-33B-GGUF

AtomicChat · Nanbeige4.3-33B-GGUF

GGUF quants of Nanbeige's Nanbeige4.3-33B, built from Nanbeige's original BF16 weights on release day. Nanbeige4.3-33B is Nanbeige's 33B dense agent and reasoning model (Llama architecture, 512K context, thinking on by default), Apache-2.0. You can now run Nanbeige4.3-33B in Atomic Chat , with thinking on by default. Atomic Dynamic (AD) files with our own importance matrix, from 13.7 GB to 30.1 GB on disk, plus plain Q8_0 and Q5_K_M ; every one measured against the BF16 original on one stand. > [!NOTE] > **Built on release day, 25 October.** `Q8_0` and `Q5_K_M` are llama.cpp's own > presets, made without an importance matrix; its `Q6_K` and `Q4_K_M` were up > for the first hours and are removed now that `AD-` files beat them at the same > size (their numbers stay below as the baseline). The `AD-` files > use our own importance matrix, collected on the BF16 weights (`--parse-special`) > over 8,000 chunks of 512 tokens of our calibration corpus. The corpus build was > rendered for Qwen3.8-27B, whose chat format (ChatML) Nanbeige4.3 shares; it is > `imatrix/imatrix.gguf` in the metrics repo.

译文排队中，当前展示来源原文。

文本生成reasoninglicense:apache-2.0
上下文窗口来源未披露
输入 → 输出文本 → 文本
模型权重待核验
档案更新时间2026/11/2 19:16:37
OVERVIEW

模型介绍

GGUF quants of Nanbeige's Nanbeige4.3-33B, built from Nanbeige's original BF16 weights on release day. Nanbeige4.3-33B is Nanbeige's 33B dense agent and reasoning model (Llama architecture, 512K context, thinking on by default), Apache-2.0. You can now run Nanbeige4.3-33B in Atomic Chat , with thinking on by default. Atomic Dynamic (AD) files with our own importance matrix, from 13.7 GB to 30.1 GB on disk, plus plain Q8_0 and Q5_K_M ; every one measured against the BF16 original on one stand. > [!NOTE] > **Built on release day, 25 October.** `Q8_0` and `Q5_K_M` are llama.cpp's own > presets, made without an importance matrix; its `Q6_K` and `Q4_K_M` were up > for the first hours and are removed now that `AD-` files beat them at the same > size (their numbers stay below as the baseline). The `AD-` files > use our own importance matrix, collected on the BF16 weights (`--parse-special`) > over 8,000 chunks of 512 tokens of our calibration corpus. The corpus build was > rendered for Qwen3.8-27B, whose chat format (ChatML) Nanbeige4.3 shares; it is > `imatrix/imatrix.gguf` in the metrics repo.

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 · AtomicChat/Nanbeige4.3-33B-GGUF ↗2026/11/1 07:54:06
huggingface · enrich:eb5996e8-79af-4a78-a9ee-c3e5573b42cd ↗2026/10/29 20:42:44

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。