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GVS5H:5个Qwen3.8-27B 在 LiveCode Bench 硬上匹配 Claude 第5号寓言的模型
GVS5H：大猩猩对5人
结果
Opus 5运行在更早的版本脚手架上，单行道通过OpenRouter服务，而不是5通被固定后端。
摘要。 边疆编码性能一般以更大型的专有型号以高成本购买。 我们采用基于分类账的零发自控方法，这是一种无训练方法，在一个模型的新实例中，通过持有计划，指出和当前解决方案的共享文件系统来分解问题并进行协调。 在100个最新的硬LiveCode Bench问题上，共有11个开放型和封闭型模型，这种方法在被固定后端产生25.6%的增益，提供了两条通往前沿准确度的路线。 管弦乐Qwen3.8 Flash Next达到93.0%通过@1对Fable 5的90.4%，成本为9%，本地服务，开放重量的Qwen3.8-27B从66.8%升至92.4%. 收益并不普遍：一些模型没有变化或更糟。 转写分析将收益归属于分解和持久性上下文。 推论时间组织可以以成本的一分之一接近前沿编码精度，或者在自负重上略为超过。
--engine多剂运行管理器；--engine单机是单调基准。
其他型号：anthropic:"model","破损镜":"model","openrouter:"model"，各有自有的"* API KEY".
传出@ 1 分数印出在结尾。 结果写入运行/结果.json，工作空间写入运行/ws/.
许可证
密码是麻省理工学院的许可文件、数字和运行数据
CC BY 4.0 (英语). LiveCode Bench 叉，基准测试问题声明
和 LaTeX 模板文件保存自己的许可证。 参见Notice.md
哪个许可证覆盖哪条路。
关于
GVS5H:5个Qwen3.8-27B 在LiveCode Bench Hard上匹配Claude Fable 5的型号。..
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GVS5H: Five Qwen3.8-27B Models Match Claude Fable 5 on LiveCodeBench Hard
GVS5H: Gorilla vs. 5 Humans
Results
Opus 5 ran on an earlier version of the scaffold, in a single pass served through OpenRouter rather than five on a pinned backend.
Abstract. Frontier coding performance is typically bought with larger proprietary models at high cost. We introduce ledger-based zero-shot self-orchestration, a training-free method in which fresh instances of one model decompose problems and coordinate through a shared filesystem holding a plan, notes and current solution. Across eleven open and closed-weight models on the 100 latest hard LiveCodeBench problems, the method yields gains of up to 25.6 percentage points on pinned backends and offers two routes to frontier-level accuracy. Orchestrated Qwen3.8 Flash Next reaches 93.0% pass@1 against Fable 5's 90.4% at 9% of the cost, and locally served, open-weight Qwen3.8-27B rises from 66.8% to 92.4%. Gains are not universal: some models are unchanged or worse. Transcript analysis attributes the gain to decomposition and persistent context. Inference-time organization can approach frontier coding accuracy at a fraction of the cost, or slightly exceed it on self-hostable weights.
--engine multiagent runs the manager; --engine single is the one-call baseline.
Other models: anthropic:<model>, dashscope:<model>, openrouter:<model>, each with its own *_API_KEY.
The pass@1 score prints at the end. Results are written to runs/results.json, workspaces to runs/ws/.
License
Code is under the MIT License. The paper, figures and run data are under
CC BY 4.0. The LiveCodeBench fork, the benchmark problem statements
and the LaTeX template files keep their own licenses. See NOTICE.md for
which license covers which path.
About
GVS5H: Five Qwen3.8-27B Models Match Claude Fable 5 on LiveCodeBench Hard | Fable 5 Level Coding for a Fifth the Price - or on a Single GPU
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