SanityBoard 新增 Qwen3.5、GLM5 及代理

• GPT-5.3-Codex employs a subagent architecture enabling simultaneous analysis of multiple implementation strategies and dynamic switching between high-level architecture planning and low-level syntax optimization[1] • Minimax M2.5 paired with Droid agent framework demonstrates modular, state-aware task decomposition that reduces iteration count and improves accuracy on algorithmic challenges[1] • SanityBoard evaluation harness is designed as a lightweight, universally compatible tool for evaluating coding agents across broad sets of programming tasks[2] • Current infrastructure limitations include 5-15 minute API delays between tasks for GLM 5 testing, constraining comprehensive multi-framework evaluation[1] • Future evaluation plans include apples-to-apples comparison of OpenAI endpoints against Anthropic systems using identical evaluation harness[1]

The shift from isolated model benchmarking to agent-system evaluation represents a maturation of AI coding assessment methodology, better reflecting real-world deployment scenarios. The competitive emergence of open-weight models (Minimax M2.5, GLM 5) alongside proprietary systems suggests the coding AI market will increasingly differentiate on agent architecture and integration rather than base model capability alone. Infrastructure scalability challenges currently limiting GLM 5 evaluation indicate that future performance rankings may shift significantly once API bottlenecks are resolved. The emphasis on open-source evaluation transparency and community participation could establish new standards for AI benchmarking credibility, potentially influencing how enterprises evaluate coding AI systems for production adoption.