GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering, and complex multi-step automation. Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning.

GLM 5.2 的费用是多少？

GLM 5.2 的费用为 US$0.006/百万输入 token 和 US$6.80/百万输出 token，Cache Read，价格为 US$0.005/M tokens 单独计费。

GLM 5.2 的上下文长度是多少？

GLM 5.2 的上下文窗口为 1,048,576 个 token。它最多支持 1,048,576 个补全 token。

GLM 5.2 是否支持工具调用和结构化输出？

是的。GLM 5.2 支持通过 tools 进行函数调用。它还支持通过 response_format 中的 JSON schema 实现结构化输出。

哪些提供商提供 GLM 5.2 服务？

GLM 5.2 在 OpenRouter 上由 24 家提供商提供服务：Wafer, Relace, Morph, Cloudflare, DeepInfra, Ambient, StreamLake, CoreWeave 及另外 16 个。请求会路由至当前可用的最佳提供商，并在故障时自动切换至其他提供商，您也可以通过提供商路由固定或排除提供商。

GLM 5.2 是何时发布的？

GLM 5.2 于 2026年6月16日发布。

GLM 5.2 - API 定价与基准测试

Name: Z.ai: GLM 5.2
Author: Z.ai

基准测试得分摘要： Z.ai: GLM 5.2 （Artificial Analysis、Design Arena 和 Vals AI）
来源	基准测试	得分
Artificial Analysis	GLM-5.2 (Max) Coding Index	68.8
Artificial Analysis	GLM-5.2 (Max) Agentic Index	38.4
Artificial Analysis	GLM-5.2 (Max) GPQA Diamond	89.5%
Artificial Analysis	GLM-5.2 (Max) HLE	41.1%
Artificial Analysis	GLM-5.2 (Max) IFBench	73.3%
Artificial Analysis	GLM-5.2 (Max) τ²-Bench Telecom	99.1%
Artificial Analysis	GLM-5.2 (Max) AA-LCR	78.3%
Artificial Analysis	GLM-5.2 (Max) τ-Bench Banking	34.6%
Artificial Analysis	GLM-5.2 (Max) GDPval-AA	44.1%
Artificial Analysis	GLM-5.2 (Max) CritPt	20.9%
Artificial Analysis	GLM-5.2 (Max) SciCode	51.2%
Artificial Analysis	GLM-5.2 (Max) Terminal-Bench Hard	50.8%
Artificial Analysis	GLM-5.2 (Max) Terminal-Bench 4.0	1.0%
Artificial Analysis	GLM-5.2 (Max) Terminal-Bench 2.1	77.9%
Artificial Analysis	GLM-5.2 (Non-reasoning) Coding Index	46.5
Artificial Analysis	GLM-5.2 (Non-reasoning) GPQA Diamond	68.6%
Artificial Analysis	GLM-5.2 (Non-reasoning) HLE	9.8%
Artificial Analysis	GLM-5.2 (Non-reasoning) AA-LCR	42.3%
Artificial Analysis	GLM-5.2 (Non-reasoning) τ-Bench Banking	16.7%
Artificial Analysis	GLM-5.2 (Non-reasoning) GDPval-AA	37.6%
Artificial Analysis	GLM-5.2 (Non-reasoning) CritPt	3.1%
Artificial Analysis	GLM-5.2 (Non-reasoning) Terminal-Bench 2.1	51.7%
Design Arena	GLM 5.2 Agents Arena Agenticgamedev Elo	1155
Design Arena	GLM 5.2 Agents Arena Androidnative Elo	1177
Design Arena	GLM 5.2 Agents Arena Blender3d Elo	983
Design Arena	GLM 5.2 Agents Arena Full Stack Elo	1241
Design Arena	GLM 5.2 Agents Arena Godotgamedev Elo	1142
Design Arena	GLM 5.2 Agents Arena Htmlslides Elo	1071
Design Arena	GLM 5.2 Agents Arena Mobile Apps Elo	1160
Design Arena	GLM 5.2 Agents Arena Pdf Elo	1213
Design Arena	GLM 5.2 Agents Arena Python-Pptxslides Elo	1148
Design Arena	GLM 5.2 Agents Arena Webapps Elo	1207
Design Arena	GLM 5.2 Models Arena 3D Elo	1284
Design Arena	GLM 5.2 Models Arena Asciiart Elo	1188
Design Arena	GLM 5.2 Models Arena Code Categories Elo	1285
Design Arena	GLM 5.2 Models Arena Data Visualization Elo	1286
Design Arena	GLM 5.2 Models Arena Game Development Elo	1266
Design Arena	GLM 5.2 Models Arena SVG Elo	1207
Design Arena	GLM 5.2 Models Arena UI Component Elo	1290
Design Arena	GLM 5.2 Models Arena Website Elo	1283
Vals AI	GLM 5.2 Code Migration	37.9%
Vals AI	GLM 5.2 CorpFin v2	66.1%
Vals AI	GLM 5.2 EMB	61.5%
Vals AI	GLM 5.2 Finance Agent (v2)	49.7%
Vals AI	GLM 5.2 GPQA Diamond	85.6%
Vals AI	GLM 5.2 Harvey's Legal Agent Benchmark v1	7.1%
Vals AI	GLM 5.2 LiveCodeBench	69.5%
Vals AI	GLM 5.2 LegalBench	84.1%
Vals AI	GLM 5.2 Legal Research Bench	31.3%
Vals AI	GLM 5.2 MedCode	40.8%
Vals AI	GLM 5.2 MedScribe	83.5%
Vals AI	GLM 5.2 MMLU Pro	86.7%
Vals AI	GLM 5.2 ProgramBench	0.5%
Vals AI	GLM 5.2 ProofBench v1	35.0%
Vals AI	GLM 5.2 SkillsBench	45.1%
Vals AI	GLM 5.2 SRE Bench	0.0%
Vals AI	GLM 5.2 SWE-bench	82.8%
Vals AI	GLM 5.2 TaxEval v2	73.3%
Vals AI	GLM 5.2 Terminal-Bench 2.1	67.8%
Vals AI	GLM 5.2 Vals Index	53.1%
Vals AI	GLM 5.2 Vibe Code Bench v1.1	64.0%


	US$0.62	US$2.42	US$0.14	0.63s	120 tps	99.90%
50% off	US$1.40US$0.70	US$4.40US$2.20	US$0.26US$0.13	0.99s	83 tps	100.00%
	US$0.006	US$6.80	US$0.005	0.38s	107 tps	100.00%
	US$0.19	US$8.00	US$0.19	0.92s	98 tps	99.95%
56% off	US$1.40US$0.6131	US$4.40US$1.927	US$0.26US$0.1139	1.12s	50 tps	100.00%
	US$0.0065	US$7.9057	US$0.0065	1.26s	84 tps	100.00%
	US$0.19	US$8.00	US$0.18	0.37s	85 tps	100.00%
	US$0.966	US$3.036	US$0.1932	0.91s	68 tps	99.51%
	US$1.40	US$4.40	US$0.26	1.47s	60 tps	100.00%
33% off	US$1.40US$0.938	US$4.40US$2.948	US$0.26US$0.1742	0.99s	58 tps	100.00%
	US$1.40	US$4.40	US$0.14	1.12s	81 tps	99.63%
25% off	US$0.75US$0.5625	US$2.40US$1.80	US$0.14US$0.105	1.48s	45 tps	99.79%
	US$1.40	US$4.40	US$0.26	0.75s	66 tps	99.59%
54% off	US$1.40US$0.6496	US$4.40US$2.042	US$0.26US$0.1206	3.00s	42 tps	99.83%
	US$1.40	US$4.40	US$0.26	1.39s	48 tps	100.00%
	US$1.12	US$3.52	US$0.224	0.89s	52 tps	94.92%
	US$1.40	US$4.40	US$0.19	0.64s	55 tps	99.53%
	US$1.40	US$4.40	US$0.26	2.83s	47 tps	99.41%
Fast	US$2.25	US$7.88	US$0.56	0.86s	80 tps	99.59%
	US$0.078	US$1.40	US$0.069	1.52s	19 tps	100.00%
	US$1.40	US$4.40	US$0.26	1.50s	93 tps	99.93%
Fast	US$2.31	US$7.26	US$0.462	0.76s	93 tps	100.00%
	US$1.40	US$4.40	US$0.26	2.28s	26 tps	100.00%
	US$0.70	US$2.20	US$0.105	1.14s	84 tps	99.79%
	US$1.40	US$4.40	US$0.14	2.86s	37 tps	98.79%
	US$1.40	US$4.40	US$0.14	12.52s	20 tps	98.63%
	US$1.40	US$4.40	US$0.26	2.25s	33 tps	99.66%
Fast	US$2.10	US$6.60	US$0.21	0.42s	201 tps	99.66%
Fast	US$2.10	US$6.60	US$0.21	0.44s	171 tps	99.64%
	US$1.40	US$4.40	US$0.14	1.16s	86 tps	65.78%
	US$0.60	US$2.00	US$0.15	75.92s	3 tps	94.95%
不用于 Standard 路由：未使用这些端点的原因
Flex25% off	US$0.60US$0.45	US$1.92US$1.44	US$0.112US$0.084	3.73s	34 tps	100.00%
	US$1.54	US$4.84	US$0.154	0.37s	93 tps	100.00%

基准测试得分摘要： Z.ai: GLM 5.2 （Artificial Analysis、Design Arena 和 Vals AI）
来源	基准测试	得分
Artificial Analysis	GLM-5.2 (Max) Coding Index	68.8
Artificial Analysis	GLM-5.2 (Max) Agentic Index	38.4
Artificial Analysis	GLM-5.2 (Max) GPQA Diamond	89.5%
Artificial Analysis	GLM-5.2 (Max) HLE	41.1%
Artificial Analysis	GLM-5.2 (Max) IFBench	73.3%
Artificial Analysis	GLM-5.2 (Max) τ²-Bench Telecom	99.1%
Artificial Analysis	GLM-5.2 (Max) AA-LCR	78.3%
Artificial Analysis	GLM-5.2 (Max) τ-Bench Banking	34.6%
Artificial Analysis	GLM-5.2 (Max) GDPval-AA	44.1%
Artificial Analysis	GLM-5.2 (Max) CritPt	20.9%
Artificial Analysis	GLM-5.2 (Max) SciCode	51.2%
Artificial Analysis	GLM-5.2 (Max) Terminal-Bench Hard	50.8%
Artificial Analysis	GLM-5.2 (Max) Terminal-Bench 4.0	1.0%
Artificial Analysis	GLM-5.2 (Max) Terminal-Bench 2.1	77.9%
Artificial Analysis	GLM-5.2 (Non-reasoning) Coding Index	46.5
Artificial Analysis	GLM-5.2 (Non-reasoning) GPQA Diamond	68.6%
Artificial Analysis	GLM-5.2 (Non-reasoning) HLE	9.8%
Artificial Analysis	GLM-5.2 (Non-reasoning) AA-LCR	42.3%
Artificial Analysis	GLM-5.2 (Non-reasoning) τ-Bench Banking	16.7%
Artificial Analysis	GLM-5.2 (Non-reasoning) GDPval-AA	37.6%
Artificial Analysis	GLM-5.2 (Non-reasoning) CritPt	3.1%
Artificial Analysis	GLM-5.2 (Non-reasoning) Terminal-Bench 2.1	51.7%
Design Arena	GLM 5.2 Agents Arena Agenticgamedev Elo	1155
Design Arena	GLM 5.2 Agents Arena Androidnative Elo	1177
Design Arena	GLM 5.2 Agents Arena Blender3d Elo	983
Design Arena	GLM 5.2 Agents Arena Full Stack Elo	1241
Design Arena	GLM 5.2 Agents Arena Godotgamedev Elo	1142
Design Arena	GLM 5.2 Agents Arena Htmlslides Elo	1071
Design Arena	GLM 5.2 Agents Arena Mobile Apps Elo	1160
Design Arena	GLM 5.2 Agents Arena Pdf Elo	1213
Design Arena	GLM 5.2 Agents Arena Python-Pptxslides Elo	1148
Design Arena	GLM 5.2 Agents Arena Webapps Elo	1207
Design Arena	GLM 5.2 Models Arena 3D Elo	1284
Design Arena	GLM 5.2 Models Arena Asciiart Elo	1188
Design Arena	GLM 5.2 Models Arena Code Categories Elo	1285
Design Arena	GLM 5.2 Models Arena Data Visualization Elo	1286
Design Arena	GLM 5.2 Models Arena Game Development Elo	1266
Design Arena	GLM 5.2 Models Arena SVG Elo	1207
Design Arena	GLM 5.2 Models Arena UI Component Elo	1290
Design Arena	GLM 5.2 Models Arena Website Elo	1283
Vals AI	GLM 5.2 Code Migration	37.9%
Vals AI	GLM 5.2 CorpFin v2	66.1%
Vals AI	GLM 5.2 EMB	61.5%
Vals AI	GLM 5.2 Finance Agent (v2)	49.7%
Vals AI	GLM 5.2 GPQA Diamond	85.6%
Vals AI	GLM 5.2 Harvey's Legal Agent Benchmark v1	7.1%
Vals AI	GLM 5.2 LiveCodeBench	69.5%
Vals AI	GLM 5.2 LegalBench	84.1%
Vals AI	GLM 5.2 Legal Research Bench	31.3%
Vals AI	GLM 5.2 MedCode	40.8%
Vals AI	GLM 5.2 MedScribe	83.5%
Vals AI	GLM 5.2 MMLU Pro	86.7%
Vals AI	GLM 5.2 ProgramBench	0.5%
Vals AI	GLM 5.2 ProofBench v1	35.0%
Vals AI	GLM 5.2 SkillsBench	45.1%
Vals AI	GLM 5.2 SRE Bench	0.0%
Vals AI	GLM 5.2 SWE-bench	82.8%
Vals AI	GLM 5.2 TaxEval v2	73.3%
Vals AI	GLM 5.2 Terminal-Bench 2.1	67.8%
Vals AI	GLM 5.2 Vals Index	53.1%
Vals AI	GLM 5.2 Vibe Code Bench v1.1	64.0%

GLM 5.3 FlashX Legal

GLM-5.3-FlashX-Legal (GLM-Legal) is Z.ai's legal-domain variant of GLM-5.3-FlashX, a native multimodal model that accepts text, image, and video input and produces text. It adds legal-domain mid-training and post-training with reinforcement learning in task environments modeled on real legal workflows, targeting document understanding, legal reasoning, and multi-step task execution such as legal research, contract review, cross-document consistency checks, and drafting or revising legal documents.

It keeps the GLM-5.3-FlashX 1M-token context window, mandatory thinking mode, function calling, structured output, and streaming, and is designed to run in agent setups connected to legal data and document-editing tools (MCP services).

文本1.0M 上下文US$0.37 / US$1.25

GLM 5.3 Prime

GLM-5.3-Prime is the high-speed variant of Z.ai's GLM-5.3, inheriting its full capabilities while delivering 1.5–2× the output throughput through inference acceleration. It supports text input and output with a 1M-token context window and up to 128K output tokens, and targets coding and agentic workloads, including long-horizon multi-turn agent orchestration, real-time conversation, and streaming code generation.

Reasoning is always on and cannot be disabled. Reasoning efforts low, high, and max are supported; max is the default.

文本1M 上下文US$2.80 / US$8.80

GLM 5.3 FlashX

GLM-5.3-FlashX is the high-speed variant of Z.ai's GLM-5.3-Flash, a native multimodal model delivering inference speeds of up to 200 tokens/s. Built on the same hybrid sparse and linear attention architecture (320B total parameters, 18B active), it is suited for efficient coding, visual understanding, and long-horizon agent tasks with a 1M-token context window.

文本1.0M 上下文US$0.37 / US$1.25

GLM Flash Latest

This model always redirects to the latest model in the GLM Flash family.

文本1.0M 上下文

GLM 5.3 Flash

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

文本1.0M 上下文US$0.0285 / US$0.0923

GLM 5.3 Flash (batch)

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

文本1.0M 上下文US$0.05 / US$0.18

GLM Latest

This model always redirects to the latest GLM model from Z.ai.

文本1.0M 上下文

GLM 5.3

GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves on GLM-5.2 in coding and in the balance between performance and token efficiency.

Reasoning is always on and cannot be disabled. Reasoning efforts low, high, and max are supported; max is the default.

文本1.0M 上下文US$0.0699 / US$1.40

GLM 5.3 (batch)

GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves on GLM-5.2 in coding and in the balance between performance and token efficiency.

Reasoning is always on and cannot be disabled. Reasoning efforts low, high, and max are supported; max is the default.

文本1.0M 上下文US$0.45 / US$2

GLM 5.1

GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on a single task for more than 8 hours, autonomously planning, executing, and improving itself throughout the process, ultimately delivering complete, engineering-grade results.

文本205K 上下文US$0.90 / US$2.90

GLM 5V Turbo

GLM-5V-Turbo is Z.ai’s first native multimodal agent foundation model, built for vision-based coding and agent-driven tasks. It natively handles image, video, and text inputs, excels at long-horizon planning, complex coding, and task execution, and works seamlessly with agents to complete the full loop of “perceive → plan → execute“.

文本203K 上下文US$1.20 / US$4

GLM 5 Turbo

GLM-5 Turbo is a new model from Z.ai designed for fast inference and strong performance in agent-driven environments such as OpenClaw scenarios. It is deeply optimized for real-world agent workflows involving long execution chains, with improved complex instruction decomposition, tool use, scheduled and persistent execution, and overall stability across extended tasks.

文本203K 上下文US$1.20 / US$4

GLM 5

GLM-5 is Z.ai’s flagship open-source foundation model engineered for complex systems design and long-horizon agent workflows. Built for expert developers, it delivers production-grade performance on large-scale programming tasks, rivaling leading closed-source models. With advanced agentic planning, deep backend reasoning, and iterative self-correction, GLM-5 moves beyond code generation to full-system construction and autonomous execution.

文本205K 上下文US$0.60 / US$1.92

GLM 4.7 Flash

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.

文本200K 上下文US$0.0605 / US$0.40

GLM 4.7

GLM-4.7 is Z.ai’s latest flagship model, featuring upgrades in two key areas: enhanced programming capabilities and more stable multi-step reasoning/execution. It demonstrates significant improvements in executing complex agent tasks while delivering more natural conversational experiences and superior front-end aesthetics.

文本205K 上下文US$0.40 / US$1.75

GLM 4.6V

GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts and charts directly as visual inputs, and integrates native multimodal function calling to connect perception with downstream tool execution. The model also enables interleaved image-text generation and UI reconstruction workflows, including screenshot-to-HTML synthesis and iterative visual editing.

文本131K 上下文US$0.30 / US$0.90

GLM 4.6

Compared with GLM-4.5, this generation brings several key improvements:

Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex agentic tasks. Superior coding performance: The model achieves higher scores on code benchmarks and demonstrates better real-world performance in applications such as Claude Code、Cline、Roo Code and Kilo Code, including improvements in generating visually polished front-end pages. Advanced reasoning: GLM-4.6 shows a clear improvement in reasoning performance and supports tool use during inference, leading to stronger overall capability. More capable agents: GLM-4.6 exhibits stronger performance in tool using and search-based agents, and integrates more effectively within agent frameworks. Refined writing: Better aligns with human preferences in style and readability, and performs more naturally in role-playing scenarios.

文本205K 上下文US$0.43 / US$1.75

GLM 4.5V

GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding, image Q&A, OCR, and document parsing, with strong gains in front-end web coding, grounding, and spatial reasoning. It offers a hybrid inference mode: a "thinking mode" for deep reasoning and a "non-thinking mode" for fast responses. Reasoning behavior can be toggled via the reasoning enabled boolean. Learn more in our docs

文本66K 上下文US$0.60 / US$1.80

GLM 4.5

GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly enhanced capabilities in reasoning, code generation, and agent alignment. It supports a hybrid inference mode with two options, a "thinking mode" designed for complex reasoning and tool use, and a "non-thinking mode" optimized for instant responses. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

文本131K 上下文US$0.60 / US$2.20

GLM 4.5 Air

GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter size. GLM-4.5-Air also supports hybrid inference modes, offering a "thinking mode" for advanced reasoning and tool use, and a "non-thinking mode" for real-time interaction. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

文本131K 上下文US$0.13 / US$0.85

Z.ai: GLM 5.2

Z.ai: GLM 5.2

提供商

定价

性能

正常运行时间

基准测试

应用

活动

API

可通过欧盟区域内路由使用

探索更多模型

提供商

定价

性能

正常运行时间

过去 3 天的可用性

过去 24 小时的可用性

基准测试

应用

活动

API

可通过欧盟区域内路由使用

常见问题

探索更多模型

更多模型，来自 Z.ai

过去 3 天的可用性

过去 24 小时的可用性

常见问题

更多模型，来自 Z.ai

Z.ai: GLM 5.2

Z.ai: GLM 5.2

提供商

定价

性能

正常运行时间

基准测试

应用

活动

API

可通过欧盟区域内路由使用

探索更多模型

提供商

定价

性能

正常运行时间

过去 3 天的可用性

过去 24 小时的可用性

基准测试

应用

活动

API

可通过欧盟区域内路由使用

常见问题

什么是 GLM 5.2？

GLM 5.2 的费用是多少？

GLM 5.2 的上下文长度是多少？

GLM 5.2 是否支持工具调用和结构化输出？

哪些提供商提供 GLM 5.2 服务？

GLM 5.2 是何时发布的？

探索更多模型

更多模型，来自 Z.ai

过去 3 天的可用性

过去 24 小时的可用性

常见问题

什么是 GLM 5.2？

GLM 5.2 的费用是多少？

GLM 5.2 的上下文长度是多少？

GLM 5.2 是否支持工具调用和结构化输出？

哪些提供商提供 GLM 5.2 服务？

GLM 5.2 是何时发布的？

更多模型，来自 Z.ai