Coding benchmarks that are quickly showcasing deep capability

While we see for frontier models similar scores among famous coding benchmarks, across: DeepSWE, Terminal-Bench, LiveCodeBench, Code-Arena ELO. Here are in my opinion some next level benchmarks that really define deep intelligence, and complete capability in Software Engineering : 1. Program-Bench Given only a compiled binary and its documentation, agents must architect and implement a complete codebase that reproduces the original program's behavior (without access to decompilers or internet). Link: https://programbench.com/ GPT-6 Astra: 5.5% Fable 5.1: 7% Kimi K3: 2% Qwen3.8 27b: 0% GPT 5.6 Sol: 1.5% GLM 5.3: 1.5% GPT 5.6 Luna: 0% 2. SRE-Bench Can AI agents work out what a real-world binary does without its source code? Link: https://www.vals.ai/benchmarks/srebench Sure nobody is reading assembly code in daily work, it is hard. The ability to understand a compiled program is insane ability. GPT-6 Astra: 88% GPT-5.6 Sol: 55.9% Claude Opus 5 (max): 12.5% 3. Code Migration Can language models reimplement working programs in another language? Link: https://www.vals.ai/benchmarks/code-migration GPT-6 Astra: 67.7% Fable 5.1: 54.6% GLM 5.3: 44.2% GLM 5.3 Flash: 20.5% Qwen3.8 27b: 14.2% EDIT: edited text format submitted by /u/Informal-Trouble2183 [link] [comments]

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• Terminal Bench 4.0 just dropped, GLM-5.3 is at the same level as Fable 5, accounting for margin of error

Source: r/LocalLLaMA | 2026-09-06