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Model details

GLM-5.2

GLM-5.2 is a large-scale open-weights reasoning model built around a Mixture-of-Experts architecture with 753B total parameters and roughly 40B active at inference, released under an MIT license after a mid-June 2026 rollout. The model is text-only on both input and output, with vision handled by a separate model family rather than bundled in. It is paired with an extended context window suited to project-scale work, and the provider positions it for long-horizon agent workflows, multi-step automation, and end-to-end software engineering tasks that need consistent engineering context from requirements through deployment.

In third-party and community testing, GLM-5.2 has drawn attention for coding and tool use, with an independent benchmark write-up reporting it ahead of a leading closed competitor and Hacker News anecdotes describing fast output and workable behavior when wired into real agent pipelines. OpenRouter exposes reasoning effort controls including high and xhigh modes for heavier deliberation, and the model is routable across multiple host providers at modest token pricing, which broadens practical access. The combination of open weights, a large MoE design, and agent-oriented strengths makes GLM-5.2 a natural fit for teams building coding assistants, autonomous tooling, and other long-running workflows where sustained reasoning and tool use matter more than multimodal breadth.

Synthetichf:zai-org/GLM-5.2glm

Quick Info

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Provider
Synthetic
Model key
hf:zai-org/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
65,536 tokens
Context window
524,288 tokens

Transparent token rates

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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

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CoverageBenchmark

A Hacker News thread (1113 points, June 29, 2026) links to Semgrep's benchmark post titled "GLM 5.2 beats Claude in our benchmarks," highlighting a third-party coding evaluation angle for GLM-5.2. A commenter from Gert Labs notes that Chinese-lab models generally show a wider gap between public benchmarks and their int Developer anecdotes in the thread corroborate real-world deployability: one user (pimeys) reports using unquantized GLM-5.2 via Fireworks to build a multimodal Rust agent for their homelab over two days for roughly $20, compared to over $100 with GPT for similar work, citing fast output and a workable personality. Anot

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Coverage

Simon Willison reports that Z.ai released GLM-5.2 to coding plan subscribers on June 13, 2026, followed by full open-weight release under an MIT license on June 16, 2026. The model is a 753B-parameter Mixture-of-Experts network with 40B active parameters, weighing 1.51TB, and expands context to 1 million tokens from GL Artificial Analysis ranks GLM-5.2 as the leading open-weights model on the Intelligence Index v4.1 with a score of 51, ahead of MiniMax-M3 (44), DeepSeek V4 Pro max (44), and Kimi K2.6 (43), while also placing second on the Code Arena WebDev leaderboard behind only Claude Fable 5. Willison notes token-usage concerns at

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CoverageAnalysis

Z.ai's GLM-5.2 is the new leading open-weights model on the Artificial Analysis Intelligence Index v4.1, scoring 51 and edging MiniMax-M3 (44), DeepSeek V4 Pro max (44), and Kimi K2.6 (43). The model retains GLM-5.1's 744B total / 40B active parameter MoE footprint and is released under an MIT license, with first-party GLM-5.2 improves over GLM-5.1 across most evaluations, with the largest gains on scientific reasoning: CritPt +16 to 21%, HLE +12 to 40%, AA-LCR +9 to 71%, tau3-banking +15 to 27%, SciCode +7 to 50%, TerminalBench v2.1 +16 to 78%, and GPQA Diamond +3 to 89%. On the agentic GDPval-AA v2 benchmark it scores 1524, ahead o

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CoverageBenchmark

Z.ai has launched GLM-5.2 with a usable 1M-token context window and two thinking-effort levels, distinguishing it from prior GLM releases. The model is positioned for long-form coding tasks, and the launch notably included no first-party benchmarks at launch time, making early third-party benchmarks the primary signal The MarkTechPost report frames GLM-5.2 as a new open-source Chinese AI model from Z.ai aimed at long-form coding tasks, with the headline technical features being the 1M-token context window and two thinking-effort tiers. Because Z.ai did not publish benchmarks at launch, downstream assessments like Artificial Analysis

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