Zhipu AI model product
GLM-5.2 is Z.AI's flagship foundation model built for long-horizon tasks, delivering a solid 1M-token context that stably sustains long, messy coding-agent trajectories. It improves substantially over GLM-5.1, becoming the strongest open-source model on standard coding benchmarks (81.0 on Terminal-Bench 2.1 and 62.1 on SWE-bench Pro) and the highest-ranked open-source model across long-horizon coding benchmarks (FrontierSWE, PostTrainBench, SWE-Marathon). It introduces flexible thinking effort levels (High and Max) to balance capability against latency and compute. Architecturally, GLM-5.2 proposes IndexShare, which reuses one lightweight indexer across every four sparse-attention (DSA) layers to cut per-token FLOPs by 2.9x at 1M context, and an improved MTP layer for speculative decoding that raises acceptance length by up to 20%. Released under a pure MIT open-source license with weights available on HuggingFace and ModelScope, it supports transformers, vLLM, SGLang, xLLM, and ktransformers, with 1M input context, 128K max output, thinking mode, function calling, structured output, context caching, and MCP integration.
Updated Aug 10, 2026. Default version: GLM-5.2
Structured fields from the published default version.
This profile uses the latest version under this unique model that has a calculated LLMBoard score. Arena and price are excluded.
Published benchmark records for the scored version GLM-5.2.
| AIME 2026 | 1.0 | 1 | 17 | 100.0% | C | |
| CritPT | 0.2 | 1 | 4 | 100.0% | C | |
| IMO-AnswerBench | 0.9 | 2 | 19 | 94.4% | C | |
| Program Bench | 0.6 | 2 | 5 | 75.0% | C | |
| NL2Repo | 0.5 | 3 | 14 | 84.6% | C | |
| PostTrainBench | 0.3 | 3 | 5 | 50.0% | C | |
| SWE-Marathon | 0.1 | 3 | 3 | 0.0% | C | |
| FrontierSWE | 0.7 | 4 | 15 | 78.6% | B | |
| HMMT Feb 26 | 0.9 | 6 | 11 | 50.0% | C | |
| DeepSWE | 0.5 | 7 | 10 | 33.3% | C | |
| HMMT 2025 | 0.9 | 9 | 33 | 75.0% | C | |
| MCP Atlas | 0.8 | 9 | 30 | 72.4% | C | |
| Terminal-Bench 2.1 | 0.8 | 9 | 17 | 50.0% | C | |
| SWE-Bench Pro | 0.6 | 11 | 44 | 76.7% | C | |
| FrontierCode 1.1 | 0.2 | 12 | 15 | 21.4% | B | |
| Humanity's Last Exam | 0.5 | 12 | 92 | 87.9% | C | |
| DeepSWE 1.1 | 0.4 | 15 | 19 | 22.2% | B | |
| GPQA | 0.9 | 18 | 233 | 92.7% | C | |
| Toolathlon | 0.5 | 18 | 31 | 43.3% | C |
Preference and agent-evaluation signals from published Arena datasets.
The default version has no published Arena rows, or its source alias has not been resolved.
Official vendor API PAYG pricing is summarized first. The table then lists individual provider offerings without treating their minimum as the official price.
| Zhipu AI Coding Plan | glm-5.2 | global | N/A | N/A | 1M | |
| Alibaba Token Plan | glm-5.2 | global | N/A | N/A | 1M | |
| Z.AI Coding Plan | glm-5.2 | global | N/A | N/A | 1M | |
| Alibaba Token Plan (China) | glm-5.2 | global | N/A | N/A | 1M | |
| CrofAI | glm-5.2 | global | $0.50 | $2.2 | 1M | |
| LLM Gateway | glm-5.2 | global | $0.55 | $1.93 | 1M | |
| DigitalOcean | glm-5.2 | global | $0.70 | $2.2 | 262.1K | |
| routing.run | glm-5.2 | global | $0.80 | $2.4 | 200K | |
| Alibaba (China) | glm-5.2 | global | $1.1 | $3.85 | 1M | |
| AIHubMix | glm-5.2 | global | $1.13 | $3.94 | 1M | |
| Vivgrid | glm-5.2 | global | $1.2 | $4.2 | 1M | |
| Wafer | GLM-5.2 | global | $1.2 | $4.1 | 1M | |
| Requesty | glm-5.2 | global | $1.2 | $4.2 | 1M | |
| Cortecs | glm-5.2 | global | $1.2 | $4.2 | 1M | |
| DInference | glm-5.2 | global | $1.25 | $3.89 | 1M | |
| GreenPT | glm-5.2 | global | $1.25 | $5.02 | 1M | |
| OpenCode Go | glm-5.2 | global | $1.4 | $4.4 | 1M | |
| OpenCode Zen | glm-5.2 | global | $1.4 | $4.4 | 1M | |
| Charm Hyper | glm-5.2 | global | $1.4 | $4.4 | 1M | |
| Z.AI | glm-5.2 | global | $1.4 | $4.4 | 1M | |
| Neuralwatt | glm-5.2 | global | $1.45 | $4.5 | 1M | |
| UnoRouter | glm-5.2 | global | $1.6 | $5.03 | 1M | |
| Scaleway | glm-5.2 | global | $1.8 | $5.5 | 256K |
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
All published versions linked to this unique model. The score columns identify the version used by the current overall ranking.
| GLM-5.2 | 80.3 | 753B | 1M | 131.1K | Yes | MIT |
A concise description based on the published model registry.
GLM-5.2 is Z.AI's flagship foundation model built for long-horizon tasks, delivering a solid 1M-token context that stably sustains long, messy coding-agent trajectories. It improves substantially over GLM-5.1, becoming the strongest open-source model on standard coding benchmarks (81.0 on Terminal-Bench 2.1 and 62.1 on SWE-bench Pro) and the highest-ranked open-source model across long-horizon coding benchmarks (FrontierSWE, PostTrainBench, SWE-Marathon). It introduces flexible thinking effort levels (High and Max) to balance capability against latency and compute. Architecturally, GLM-5.2 proposes IndexShare, which reuses one lightweight indexer across every four sparse-attention (DSA) layers to cut per-token FLOPs by 2.9x at 1M context, and an improved MTP layer for speculative decoding that raises acceptance length by up to 20%. Released under a pure MIT open-source license with weights available on HuggingFace and ModelScope, it supports transformers, vLLM, SGLang, xLLM, and ktransformers, with 1M input context, 128K max output, thinking mode, function calling, structured output, context caching, and MCP integration.
Use the benchmark, Arena and pricing sections above as separate evidence. A missing field means the current data snapshot does not support that claim.
Data snapshot: 2026-08-07. Editorial model content is not available in the backend.
Open a comparison with the three ranked models immediately above and below this model.
Recommendations prioritize the same model type and family, then the closest published LLMBoard score.
Common questions about GLM 5.2.
GLM 5.2's default version was released on Jun 16, 2026.
No official standard PAYG price is currently available for GLM 5.2. The lowest tracked third-party offer starts at $0.50 input and $2.2 output via CrofAI.
GLM 5.2 is published under Zhipu AI in the model registry.
The default version has a 1M token context window.
Yes. The default version is marked as open weight under MIT.
25 published provider offerings are linked to the default version.
Nearby ranked alternatives include Kimi K2.6, Gemini 3 Pro, Seed 2.1 Turbo.