Kimi K2.6(Kimi for Coding)
A top-tier result with 54/151 tasks solved at least once and 32/151 solved in all three attempts; strongest around automation and configuration-management work plus large Python/Django application repairs. 这是一个第一梯队结果：151 题中至少一次解出 54 题，三次都解出 32 题；强项主要落在自动化和配置管理类改动以及大型 Python/Django 应用修复。
How to read this result可以这样读
- Kimi K2.6(Kimi for Coding) is best read as front-runner with a balanced profile: rank #5, 54 reached tasks, 32 stable solves.Kimi K2.6(Kimi for Coding) 更适合读成第一梯队里的均衡型：排名 #5，触达 54 题，稳定解出 32 题。
- Best suite signal: Ansible · release 003 at 9/10 (90.0%).最强 suite 信号：Ansible 自动化 · release 003，9/10（90.0%）。
- Weakest visible area: qutebrowser · release 018 at 0/9 (0.0%).最弱可见区域：qutebrowser 浏览器 · release 018，0/9（0.0%）。
- This row should be read as the behavior of the model inside its specific coding-agent shell.这一行应读作该模型在特定 coding-agent shell 里的行为。
Kimi K2.6(Kimi for Coding) belongs in the leading cluster because it keeps both breadth and stability in play: 54 reached tasks, 32 stable solves, and a 35.45 Final Score.
With no close provider sibling on this board, the more useful comparison is against the neighboring ranks: the row is defined by 27.8% attempt-level accuracy rather than a single standout suite.
The suite split is asymmetric: Ansible · release 003 at 9/10 (90.0%) supplies the main body of wins, vuls · release 012 at 4/4 (100.0%) supplies the clean spike, and qutebrowser · release 018 at 0/9 (0.0%) is where that pattern stops. This row should be read as the behavior of the model inside its specific coding-agent shell.
At the front of the board, the chart is a fingerprint. The score is close to peers, so the repo distribution says more than the rank delta.
The cases are useful because top rows can look similar in aggregate. Severity values from Debian Security Tracker differ between repeated scans shows the reliable core; vuls report fails to parse legacy scan results due to incompatible listenPorts field format shows the remaining edge of variance.
The verifier audit keeps 126/126 solved attempts for Kimi K2.6(Kimi for Coding), so the interesting question is not score inflation; it is where the model repeatedly finds the same kind of patch.
The available audit keeps 126 of 126 initial solved attempts. Read this as a robustness check, especially when the audit sample is smaller than 453 attempts.当前可用复核保留了 126 次初始成功中的 126 次。这更适合作为稳健性检查，特别是在复核样本小于 453 次尝试时。
In practice, read it through the gap between Ansible · release 003 at 9/10 (90.0%) and qutebrowser · release 018 at 0/9 (0.0%). That gap is more actionable than the rank because it says which repo shape gets coherent patches. The 126/453 attempt score is the backdrop; the article above is about which parts of that score are repeatable enough to matter.
Supporting suite table
| Suite | Repo | Solved | Pass^3 | Rate |
|---|---|---|---|---|
release-zh-012-future-architect-vuls |
future-architect/vuls | 4/4 | 3 | 100.0% |
release-zh-003-ansible-ansible |
ansible/ansible | 9/10 | 5 | 90.0% |
release-zh-010-future-architect-vuls |
future-architect/vuls | 7/10 | 3 | 70.0% |
release-zh-014-internetarchive-openlibrary |
internetarchive/openlibrary | 7/10 | 4 | 70.0% |
release-zh-013-internetarchive-openlibrary |
internetarchive/openlibrary | 6/10 | 5 | 60.0% |
release-zh-011-future-architect-vuls |
future-architect/vuls | 4/10 | 2 | 40.0% |
release-zh-018-qutebrowser-qutebrowser |
qutebrowser/qutebrowser | 0/9 | 0 | 0.0% |
release-zh-016-internetarchive-openlibrary |
internetarchive/openlibrary | 0/5 | 0 | 0.0% |
release-zh-017-navidrome-navidrome |
navidrome/navidrome | 0/5 | 0 | 0.0% |
release-zh-005-flipt-io-flipt |
flipt-io/flipt | 1/10 | 0 | 10.0% |
Kimi K2.6(Kimi for Coding) 能进入第一梯队，是因为覆盖和稳定性都没有掉队：至少一次解出 54 题，稳定解出 32 题，Final Score 35.45。
这个 provider 在榜单上没有特别近的同系兄弟，因此更适合和相邻排名比较：这一行的基本面是 27.8% 的单次尝试成功率，而不是某一个 suite 的孤立爆发。
suite 分布是不对称的：Ansible 自动化 · release 003，9/10（90.0%）贡献主要胜利，vuls 漏洞扫描器 · release 012，4/4（100.0%）贡献最干净高点，而qutebrowser 浏览器 · release 018，0/9（0.0%）标出这种模式停止的地方。这一行应读作该模型在特定 coding-agent shell 里的行为。
在榜单前排，这张图更像指纹。分数和相邻模型很接近，因此代码库分布比分差更说明问题。
前排模型在总分上容易看起来相似，所以案例很关键：Debian Security Tracker 的 severity 值在重复扫描之间不同 展示可靠核心，vuls report fails to parse legacy scan results due to incompatible listenPorts field format 展示剩余波动边界。
Kimi K2.6(Kimi for Coding) 的复核保留了 126 次成功中的 126 次，所以重点不是分数膨胀，而是模型在哪些地方能反复找到同类补丁。
The available audit keeps 126 of 126 initial solved attempts. Read this as a robustness check, especially when the audit sample is smaller than 453 attempts.当前可用复核保留了 126 次初始成功中的 126 次。这更适合作为稳健性检查，特别是在复核样本小于 453 次尝试时。
实际选择时，更应该通过Ansible 自动化 · release 003，9/10（90.0%）和qutebrowser 浏览器 · release 018，0/9（0.0%）之间的落差来读它。这个落差比分数排名更可操作，因为它说明哪类代码库更容易得到连贯补丁。126/453 的单次尝试成功数只是背景；上面的文章重点是哪些部分足够可重复、值得当成能力看。
支撑这个判断的 suite 表
| Suite | Repo | 解出 | Pass^3 | 通过率 |
|---|---|---|---|---|
release-zh-012-future-architect-vuls |
future-architect/vuls | 4/4 | 3 | 100.0% |
release-zh-003-ansible-ansible |
ansible/ansible | 9/10 | 5 | 90.0% |
release-zh-010-future-architect-vuls |
future-architect/vuls | 7/10 | 3 | 70.0% |
release-zh-014-internetarchive-openlibrary |
internetarchive/openlibrary | 7/10 | 4 | 70.0% |
release-zh-013-internetarchive-openlibrary |
internetarchive/openlibrary | 6/10 | 5 | 60.0% |
release-zh-011-future-architect-vuls |
future-architect/vuls | 4/10 | 2 | 40.0% |
release-zh-018-qutebrowser-qutebrowser |
qutebrowser/qutebrowser | 0/9 | 0 | 0.0% |
release-zh-016-internetarchive-openlibrary |
internetarchive/openlibrary | 0/5 | 0 | 0.0% |
release-zh-017-navidrome-navidrome |
navidrome/navidrome | 0/5 | 0 | 0.0% |
release-zh-005-flipt-io-flipt |
flipt-io/flipt | 1/10 | 0 | 10.0% |