MODEL PROFILE · 模型档案

KAT-Coder-V2.5-Dev-REAP-50-NVFP4A16

Ttimms · KAT-Coder-V2.5-Dev-REAP-50-NVFP4A16

**REAP expert-pruned (50%) + NVFP4A16 quantized build of `Kwaipilot/KAT-Coder-V2.5-Dev` (69.40 SWE-bench Verified claimed), sized and served to run as a local agentic coding model inside 16 GB of consumer VRAM** — 12.45 GiB, RTX 5070 Ti (SM120), vLLM. Built with a router-renormalization fix for this architecture (contributed upstream) and a vision tower stripped of its untrained weights. **Methodology** — how this and the sibling 16 GB builds are pruned, quantized, and evaluated (with the failure modes): **SWE-bench Verified: 26/50 = 52.0% resolved**, via `mini-swe-agent`'s official bash-only scaffold, at a 49K-token context ceiling — up from 40.0% at the original 32K ceiling tested on this same checkpoint. Still below the 56.4% bar set by Devstral Small (2512) under the same scaffold, but closed most of the gap. 17 of 50 instances produced no usable patch, all from hitting the context ceiling; the run must still be read as context-limited, not as an unconditional capability measurement. See "SWE-bench Verified" below before citing the headline number without that context.

译文排队中,当前展示来源原文。

文本生成license: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 19:15:51
OVERVIEW

模型介绍

**REAP expert-pruned (50%) + NVFP4A16 quantized build of `Kwaipilot/KAT-Coder-V2.5-Dev` (69.40 SWE-bench Verified claimed), sized and served to run as a local agentic coding model inside 16 GB of consumer VRAM** — 12.45 GiB, RTX 5070 Ti (SM120), vLLM. Built with a router-renormalization fix for this architecture (contributed upstream) and a vision tower stripped of its untrained weights. **Methodology** — how this and the sibling 16 GB builds are pruned, quantized, and evaluated (with the failure modes): **SWE-bench Verified: 26/50 = 52.0% resolved**, via `mini-swe-agent`'s official bash-only scaffold, at a 49K-token context ceiling — up from 40.0% at the original 32K ceiling tested on this same checkpoint. Still below the 56.4% bar set by Devstral Small (2512) under the same scaffold, but closed most of the gap. 17 of 50 instances produced no usable patch, all from hitting the context ceiling; the run must still be read as context-limited, not as an unconditional capability measurement. See "SWE-bench Verified" below before citing the headline number without that context.

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

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。