GLM-5.2

This Ofox post primarily covers the GLM 5.3 API, but it confirms a key GLM-5.2 data point by anchoring the family's pricing: Z.ai's table now carries a GLM-5.3 row at $1.40 input, $0.26 cached input, and $4.40 output per million tokens — matching GLM 5.2 and GLM 5.1 line for line. The $0.26 cached input rate is 19% of For GLM-5.2-era developers still on older base URLs, the page warns that anything written in the first 24 hours after the GLM-5.x announcement quoted a base URL that did not ship, and that current Z.ai endpoints expose three protocols (OpenAI Chat Completions, OpenAI Responses, Anthropic Messages) with a documented inc

On August 14, 2026, Z.ai published a research post on GLM-5.3, explicitly stating that GLM-5.3 uses the same base model as GLM-5.2 and that every reported gain over GLM-5.2 comes from post-training rather than a new base. The post describes scaling the GLM-5.2 stack: IndexShare for efficient long-context processing, SA The same post frames GLM-5.3 as the most capable open-weights coding model Z.ai has released, claiming a 50% improvement over GLM-5.2 on the in-house Z.ai Code Bench and open-source state-of-the-art results on Terminal Bench 3.0 and Agents' Last Exam. It also reports state-of-the-art performance on CyberGym for vulnera

Z.ai has officially introduced GLM-5.2, its flagship model purpose-built for long-horizon tasks and a substantial leap over GLM-5.1, delivering for the first time a solid 1M-token context window that the company says remains reliable under real engineering pressure. The model is released under an MIT open-source licens Architecturally, GLM-5.2 introduces IndexShare, which reuses the same indexer across every four sparse-attention layers to cut per-token FLOPs by 2.9× at a 1M context length, alongside an improved MTP layer that increases speculative-decoding acceptance length by up to 20%. The team substantially expanded 1M-context tr

Ofox's integration guide shows how to wire GLM-5.2 into the Cline coding agent as a full agent — file reads, diff proposals, command execution — across the model's full 1M-token context by using Cline's OpenAI Compatible provider (not its Anthropic slot, which is reserved for Claude models). The guide flags two practic On cost, the guide reports GLM-5.2 is roughly 1.6–1.9x cheaper than Claude Sonnet 5 on raw per-token rates, with caching narrowing the gap, and recommends GLM-5.2 when Cline sessions are long, file-heavy, and token-volume-driven, while steering readers away when they rely on Claude-native tool use or cache controls. Th

Ofox's cost-modeling comparison puts GLM-5.2 at $1.40 input / $4.40 output per million tokens and GPT-5.5 at $5 / $30 on the same ofox.ai OpenAI-compatible endpoint, yielding a 5.56x blended cost ratio at a 2:1 I/O mix ($2.40 vs $13.33 per million tokens) and a 6.82x ratio on pure output tokens. At 100K requests per da The piece recommends GLM-5.2 for cost-sensitive batch coding agents, long-context refactor work, and output-heavy code generation pipelines where input cost and output cost both favor it, and reserves GPT-5.5 for Codex CLI / Terminal-Bench-heavy agentic workflows (citing 82.7% Terminal-Bench 2.1), latency-sensitive int

VentureBeat reported on June 16, 2026 that Z.ai released GLM-5.2, a 753-billion-parameter open-weights LLM targeted at long-horizon autonomous coding and engineering. According to the article, GLM-5.2 became available immediately on Hugging Face, the Z.ai API, and more than 20 third-party coding environments, with ente The article corroborates Z.ai's technical claims: a 1-million-token context window, the new IndexShare attention optimization that reuses one indexer across every four sparse attention layers and reduces per-token FLOPs by 2.9× at maximum context, and an upgraded Multi-Token Prediction layer that boosts speculative-dec