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Model details

GLM-5.2

GLM-5.2 is a Z.ai coding model built around a 753-billion-parameter mixture-of-experts architecture, making it well suited to long-context software work and tool-driven agent tasks. It is open-weight under the MIT license, allowing organizations with sufficient hardware to self-host rather than depend on a hosted service.

The model’s practical appeal is its combination of repository-scale context, tool calling, and always-on reasoning that can be tuned by effort. It is a strong fit for code review, refactoring, batch generation, and other sustained engineering workflows, especially where teams can use its open weights for deployment control and keep an eye on reasoning-token usage.

TokenGoz-ai/glm-5.2glm

Quick Info

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Provider
TokenGo
Model key
z-ai/glm-5.2
Release date
Jun 13, 2026
Last updated
Jun 13, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$1.40
Output token cost
$4.40

Limits

Output tokens
131,072 tokens
Context window
1,000,000 tokens

Transparent token rates

Compare GLM-5.2 pricing

Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about GLM-5.2

Ofox

Official sourceAnnouncement

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

OrcaRouter

Official sourceAnnouncement

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

TokenGo

CoverageBenchmark

Morph's August 21, 2026 article (last updated August 28, 2026) documents GLM-5.3 as Z.ai's August 14, 2026 upgrade of GLM-5.2, built on the same 753B mixture-of-experts base with no new pretraining — all gains from scaled post-training. Terminal-Bench 3.0 jumped from 4.6 to 28.3, DeepSWE v1.1 from 46.2 to 66.9, and Cyb GLM-5.3 ships as a post-training-only upgrade aimed at long-horizon agentic coding and cyber defense, with 1M context, 128K max output, and always-on reasoning (low/high/max effort, default max) that cannot be disabled. The Morph-deployed checkpoint incoai/GLM-5.3-NVFP4 is a ModelOpt NVFP4 expert quant with FP8 KV cach

TokenGo

Coverage

Simon Willison's June 17, 2026 review notes that Z.ai released GLM-5.2 to coding plan subscribers on June 13 and then released full open weights under an MIT license on June 16, describing the 753B-parameter, 1.51TB MoE model (40 active parameters) as a text-input-only model with a 1-million-token context window, up fr The review highlights GLM-5.2 ranking 2nd on the Code Arena WebDev leaderboard (behind Claude Fable 5) for front-end web development including agentic coding workflows, and notes OpenRouter availability from 9 different providers at $1.40/M input and $4.40/M output, compared to GPT-5.5 at $5/$30 and Claude Opus 4.5-4.8

OpenRouter

CoverageBenchmark

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

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