How much does GLM 5.2 cost?

GLM 5.2 costs $0.0066/M input tokens and $7.983/M output tokens, with separate rates for Cache Read at $0.0066/M tokens.

What is the context length of GLM 5.2?

GLM 5.2 has a 1,048,576 token context window. It supports up to 131,072 completion tokens.

Does GLM 5.2 support tool calling and structured outputs?

Yes. GLM 5.2 accepts tools for function calling. It also supports structured outputs via a JSON schema in response_format.

Which providers serve GLM 5.2?

GLM 5.2 is served by 24 providers on OpenRouter: Relace, Wafer, Baidu Qianfan (fp8), Cloudflare, StreamLake, DeepInfra, Ambient, CoreWeave and 16 more. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

When was GLM 5.2 released?

GLM 5.2 was released on June 16, 2026.

Z.ai: GLM 5.2

z-ai/glm-5.2

Model weights

Compare

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. It is particularly strong at coding and tool use across long-running tasks, able to maintain engineering context and follow standards consistently through a full development workflow, from requirements to multi-platform deployment, in a single task.

Modalities

In / out price

$0.0066 / $7.983per 1M

Context

1.0M

Released

Jun 16, 2026

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Latency / throughput


	$0.62	$2.42	$0.14	0.62s	136 tok/s	99.89%
	$0.007	$6.80	$0.006	0.44s	104 tok/s	100.00%
87% off	$1.40$0.189	$4.40$0.594	$0.26$0.0351	1.06s	61 tok/s	99.93%
	$1.40	$4.40	$0.26	0.34s	143 tok/s	99.89%
	$0.19	$8.00	$0.18	0.47s	105 tok/s	100.00%
	$1.54	$4.84	$0.154	0.74s	186 tok/s	99.59%
	$0.643	$1.978	$0.217	0.56s	71 tok/s	99.82%
80% off	$1.40$0.28	$4.40$0.88	$0.26$0.052	1.25s	54 tok/s	100.00%
	$0.70	$2.20	$0.105	0.60s	101 tok/s	99.68%
	$0.19	$8.00	$0.19	0.90s	94 tok/s	100.00%
	$0.0066	$7.9833	$0.0066	1.21s	82 tok/s	99.92%
50% off	$1.302$0.651	$4.092$2.046	$0.26$0.13	1.24s	66 tok/s	99.97%
	$1.40	$4.40	$0.26	0.63s	138 tok/s	98.73%
	$1.40	$4.40	$0.14	1.77s	85 tok/s	100.00%
	$1.40	$4.40	$0.26	0.33s	85 tok/s	99.64%
	$1.40	$4.40	$0.14	1.23s	91 tok/s	99.66%
	$1.40	$4.40	$0.26	0.69s	102 tok/s	100.00%
25% off	$0.75$0.5625	$2.40$1.80	$0.14$0.105	0.88s	52 tok/s	99.49%
	$0.966	$3.036	$0.1932	1.18s	68 tok/s	98.26%
	$1.40	$4.40	$0.26	0.99s	78 tok/s	100.00%
	$1.12	$3.52	$0.224	1.20s	61 tok/s	100.00%
Fast	$2.10	$6.60	$0.21	0.31s	229 tok/s	99.80%
33% off	$1.40$0.938	$4.40$2.948	$0.26$0.1742	1.40s	53 tok/s	99.47%
	$1.40	$4.40	$0.14	0.66s	82 tok/s	90.30%
	$1.40	$4.40	$0.14	1.87s	45 tok/s	100.00%
	$1.40	$4.40	$0.26	2.94s	59 tok/s	97.72%
Fast	$2.25	$7.88	$0.56	0.70s	99 tok/s	100.00%
Fast	$2.31	$7.26	$0.462	1.21s	118 tok/s	100.00%
54% off	$1.40$0.6496	$4.40$2.042	$0.26$0.1206	1.98s	88 tok/s	99.97%
Fast	$2.10	$6.60	$0.21	0.38s	137 tok/s	99.89%
	$1.40	$4.40	$0.26	2.71s	46 tok/s	100.00%
	$0.60	$2.00	$0.15	43.40s	58 tok/s	77.53%
Not used in Standard routing:Why these endpoints are not used
Flex25% off	$0.60$0.45	$1.92$1.44	$0.112$0.084	1.99s	59 tok/s	100.00%

Input $0.62Output $2.42
136 tok/s99.89% uptime
Input $0.007Output $6.80
104 tok/s100.00% uptime
Input $0.189Output $0.594
87% off
61 tok/s99.93% uptime
Input $1.40Output $4.40
143 tok/s99.89% uptime
Input $0.19Output $8.00
105 tok/s100.00% uptime
Input $1.54Output $4.84
186 tok/s99.59% uptime
Input $0.643Output $1.978
71 tok/s99.82% uptime
Input $0.28Output $0.88
80% off
54 tok/s100.00% uptime
Input $0.70Output $2.20
101 tok/s99.68% uptime
Input $0.19Output $8.00
94 tok/s100.00% uptime
Input $0.0066Output $7.9833
82 tok/s99.92% uptime
Input $0.651Output $2.046
50% off
66 tok/s99.97% uptime
Input $1.40Output $4.40
138 tok/s98.73% uptime
Input $1.40Output $4.40
85 tok/s100.00% uptime
Input $1.40Output $4.40
85 tok/s99.64% uptime
Input $1.40Output $4.40
91 tok/s99.66% uptime
Input $1.40Output $4.40
102 tok/s100.00% uptime
Input $0.5625Output $1.80
25% off
52 tok/s99.49% uptime
Input $0.966Output $3.036
68 tok/s98.26% uptime
Input $1.40Output $4.40
78 tok/s100.00% uptime
Input $1.12Output $3.52
61 tok/s100.00% uptime
Input $2.10Output $6.60
Fast
229 tok/s99.80% uptime
Input $0.938Output $2.948
33% off
53 tok/s99.47% uptime
Input $1.40Output $4.40
82 tok/s90.30% uptime
Input $1.40Output $4.40
45 tok/s100.00% uptime
Input $1.40Output $4.40
59 tok/s97.72% uptime
Input $2.25Output $7.88
Fast
99 tok/s100.00% uptime
Input $2.31Output $7.26
Fast
118 tok/s100.00% uptime
Input $0.6496Output $2.042
54% off
88 tok/s99.97% uptime
Input $2.10Output $6.60
Fast
137 tok/s99.89% uptime
Input $1.40Output $4.40
46 tok/s100.00% uptime
Input $0.60Output $2.00
58 tok/s77.53% uptime
Not used in Standard routing:Why these endpoints are not used
Input $0.45Output $1.44
Flex
1 more label
59 tok/s100.00% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.2322/M tokens

Output

$3.73/M tokens

GLM 5.2 — Price history

Price history

No effective price data for this selection

		$0.00613	$6.800	86.4%	20.6%
		$0.00659	$7.983	81.7%	2.8%
		$0.07716	$0.879	89.0%	6.4%
		$0.08284	$0.593	69.0%	9.5%
		$0.18096	$8.000	90.3%	7.4%
		$0.18997	$8.000	70.8%	0.4%
		$0.21441	$2.200	81.6%	0.5%
		$0.22179	$2.048	82.4%	1.5%
		$0.26316	$2.420	74.3%	21.3%
		$0.27448	$2.043	71.2%	3.5%
		$0.29809	$1.809	58.0%	2.1%
		$0.30786	$3.036	85.2%	0.2%
		$0.33735	$2.947	78.6%	0.0%
		$0.33763	$1.922	69.3%	0.6%
		$0.39053	$4.399	80.1%	0.3%
		$0.40662	$4.840	81.8%	1.0%
		$0.43139	$4.399	85.0%	4.9%
		$0.45730	$4.399	82.7%	2.0%
		$0.48603	$4.400	72.5%	1.8%
	Fast	$0.51483	$7.260	97.1%	4.0%
		$0.51839	$4.399	77.3%	0.7%
		$0.55988	$3.519	62.5%	0.1%
		$0.57288	$4.400	72.6%	2.2%
	Fast	$0.60614	$6.600	79.0%	0.4%
		$0.61751	$4.399	62.1%	0.8%
		$0.63394	$4.400	67.2%	0.4%
	Fast	$0.75563	$6.600	71.1%	0.5%
		$0.82874	$4.399	50.1%	0.0%
		$0.83053	$4.400	50.0%	1.9%
		$0.84625	$4.399	43.9%	1.7%
	Fast	$1.40814	$7.879	49.8%	0.1%
		$0.51136	$2.000	19.7%	0.1%
Not used in Standard routing:Why these endpoints are not used
	Flex	$0.26083	$1.439	51.7%	0.1%

Effective in $0.00613Effective out $6.800
Token share
20.6%
Effective in $0.00659Effective out $7.983
Token share
2.8%
Effective in $0.07716Effective out $0.879
Token share
6.4%
Effective in $0.08284Effective out $0.593
Token share
9.5%
Effective in $0.18096Effective out $8.000
Token share
7.4%
Effective in $0.18997Effective out $8.000
Token share
0.4%
Effective in $0.21441Effective out $2.200
Token share
0.5%
Effective in $0.22179Effective out $2.048
Token share
1.5%
Effective in $0.26316Effective out $2.420
Token share
21.3%
Effective in $0.27448Effective out $2.043
Token share
3.5%
Effective in $0.29809Effective out $1.809
Token share
2.1%
Effective in $0.30786Effective out $3.036
Token share
0.2%
Effective in $0.33735Effective out $2.947
Token share
0.0%
Effective in $0.33763Effective out $1.922
Token share
0.6%
Effective in $0.39053Effective out $4.399
Token share
0.3%
Effective in $0.40662Effective out $4.840
Token share
1.0%
Effective in $0.43139Effective out $4.399
Token share
4.9%
Effective in $0.45730Effective out $4.399
Token share
2.0%
Effective in $0.48603Effective out $4.400
Token share
1.8%
Effective in $0.51483Effective out $7.260
FastToken share
4.0%
Effective in $0.51839Effective out $4.399
Token share
0.7%
Effective in $0.55988Effective out $3.519
Token share
0.1%
Effective in $0.57288Effective out $4.400
Token share
2.2%
Effective in $0.60614Effective out $6.600
FastToken share
0.4%
Effective in $0.61751Effective out $4.399
Token share
0.8%
Effective in $0.63394Effective out $4.400
Token share
0.4%
Effective in $0.75563Effective out $6.600
FastToken share
0.5%
Effective in $0.82874Effective out $4.399
Token share
0.0%
Effective in $0.83053Effective out $4.400
Token share
1.9%
Effective in $0.84625Effective out $4.399
Token share
1.7%
Effective in $1.40814Effective out $7.879
FastToken share
0.1%
Effective in $0.51136Effective out $2.000
Token share
0.1%
Not used in Standard routing:Why these endpoints are not used
Effective in $0.26083Effective out $1.439
FlexToken share
0.1%

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput

229tok/s

P50, best across providers

Latency

0.31s

P50, best provider

Reasoning effortLatency / throughput

AutoExacto benchmarks

GPQA DiamondTAU-BenchDigitalOcean90.5%75.2%Morph85.3%77.2%Wafer (US)89.6%71.6%DeepInfra91.0%68.4%Alibaba Cloud Int. (US)86.8%72.4%Alibaba Cloud Int.87.6%71.4%Wafer88.7%69.8%Alibaba Cloud Int. (Fast)84.0%69.1%

+22 more providers

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

99.82%

Availability over the last 3 days

Last 72 hours

Availability 99.82%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.90%

Without Routing

98.29%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Z.ai: GLM 5.2 (Artificial Analysis, Design Arena and Vals AI)
Source	Benchmark	Score
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	44.0%
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 (Max) AA-Omniscience Accuracy	21.1%
Artificial Analysis	GLM-5.2 (Max) AA-Omniscience Non-Hallucination Rate	74.1%
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	1153
Design Arena	GLM 5.2 Agents Arena Androidnative Elo	1170
Design Arena	GLM 5.2 Agents Arena Blender3d Elo	983
Design Arena	GLM 5.2 Agents Arena Full Stack Elo	1213
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	1153
Design Arena	GLM 5.2 Agents Arena Pdf Elo	1242
Design Arena	GLM 5.2 Agents Arena Python-Pptxslides Elo	1161
Design Arena	GLM 5.2 Agents Arena Spreadsheet Elo	1011
Design Arena	GLM 5.2 Agents Arena Webapps Elo	1200
Design Arena	GLM 5.2 Models Arena 3D Elo	1266
Design Arena	GLM 5.2 Models Arena Asciiart Elo	1185
Design Arena	GLM 5.2 Models Arena Code Categories Elo	1277
Design Arena	GLM 5.2 Models Arena Data Visualization Elo	1282
Design Arena	GLM 5.2 Models Arena Game Development Elo	1256
Design Arena	GLM 5.2 Models Arena SVG Elo	1195
Design Arena	GLM 5.2 Models Arena UI Component Elo	1286
Design Arena	GLM 5.2 Models Arena Website Elo	1277
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%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

HighLevel

new

1.37Ttokens

Hermes Agent

Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.

207Btokens

Janitor AI

Janitor AI is a chatbot platform where users create and chat with custom AI characters for interactive roleplay, storytelling, and immersive fiction.

56.8Btokens

OpenClaw

OpenClaw is an open-source AI agent that connects to your messaging apps and takes real actions on your behalf, from running commands and browsing the web to managing files and sending emails.

54.1Btokens

ISEKAI ZERO

AI adventures. Travel with your favorite characters

43.6Btokens

Rest of OpenRouter

36.6B

Top 5 Apps

29B

Available through EU in-region routing

Z.ai: GLM 5.2 is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).

Providers in Europe

Inceptron, Mistral

Prices in Europe

Inceptron: $1.40/M tokens input, $4.40/M tokens output
Mistral: $1.54/M tokens input, $4.84/M tokens output

Base URL

https://eu.openrouter.ai/api/v1

Plan

Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing

Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs

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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).

Text1.0M context$0.37 / $1.25

GLM 5.3 Prime

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GLM 5.3 FlashX

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GLM Flash Latest

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

Text1.0M context

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GLM 5.3 Flash (batch)

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GLM Latest

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

Text1.0M context

GLM 5.3

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

Text1.0M context$0.0699 / $1.40

GLM 5.3 (batch)

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

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GLM 5.2

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Text205K context$0.60 / $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.

Text200K context$0.0605 / $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.

Text205K context$0.40 / $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.

Text131K context$0.30 / $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.

Text205K context$0.43 / $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

Text66K context$0.60 / $1.80

Z.ai: GLM 5.2

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