GLM-5 lands, sparks AGI chatter

The AGI meme is overcooked, but GLM-5 looks like a genuinely interesting open-weight release for builders who care about agent loops, not just chat quality. If the claims hold up outside the lab, it matters more as a practical alternative than as an AGI milestone.

• –Z.ai positions GLM-5 as its flagship foundation model for agentic engineering, with DeepSeek Sparse Attention and async RL (“slime”) to improve token efficiency and long-horizon learning.
• –The docs cite 77.8 SWE-bench Verified and 56.2 Terminal Bench 2.0, plus top open-model results on BrowseComp, MCP-Atlas, and τ²-Bench.
• –Product Hunt frames it as an open-weights model for long-horizon agentic engineering, which explains why coding-tool builders are paying attention immediately.
• –Reddit feedback is enthusiastic but grounded: users are comparing it with Qwen 3.5, while others point out the hardware and context-window cost of running it well.