Where is the GLM 5.3 (batch) documentation?

The GLM 5.3 (batch) documentation on OpenRouter includes the Self-Hosted LLM vs API: When Does Self-Hosting Pay Off blog post and the How to Benchmark LLMs blog post. The quickstart covers API keys and your first request, and the API reference lists every parameter.

How much does GLM 5.3 (batch) cost?

GLM 5.3 (batch) costs $0.45/M input tokens and $2.00/M output tokens, with separate rates for Cache Read at $0.10/M tokens.

What is the context length of GLM 5.3 (batch)?

GLM 5.3 (batch) has a 1,048,576 token context window. It supports up to 131,072 completion tokens.

Does GLM 5.3 (batch) support tool calling and structured outputs?

Yes. GLM 5.3 (batch) accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

Which providers serve GLM 5.3 (batch)?

GLM 5.3 (batch) is served by 2 providers on OpenRouter: DeepInfra and Together. 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 5.3 (batch) released?

GLM 5.3 (batch) was released on August 18, 2026.

Z.ai: GLM 5.3 (batch)

z-ai/glm-5.3:batch

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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.

Modalities

In / out price

38% off

$0.45 / $2per 1M

Context

1.0M

Released

Aug 18, 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).


38% off	$0.72$0.45	$3.20$2.00	$0.16$0.10	--	--	--
	$0.70	$2.20	$0.13	--	--	--

Input $0.45Output $2.00
38% off
-- tok/s-- uptime
Input $0.70Output $2.20
-- tok/s-- 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/M tokens

Output

$0/M tokens

GLM 5.3 (batch) — Price history

Price history

No effective price data for this selection

		$0.00	$0.00	22.0%	100.0%
		$0.00	$0.00	0.0%	0.0%

Effective in $0.00Effective out $0.00
Token share
100.0%
Effective in $0.00Effective out $0.00
Token share
0.0%

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).

Reasoning effort

AutoExacto benchmarks

GPQA DiamondTAU-BenchBaseten84.7%83.7%Wafer88.4%78.7%Wafer87.6%79.1%Doubleword88.6%78.0%Z.AI88.4%77.4%DeepInfra87.0%78.1%Baseten84.0%76.6%Baseten84.0%76.2%Baseten84.6%70.4%

+39 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.

Not enough uptime data to display yet.

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 5.3 (batch) (Artificial Analysis, Design Arena and Vals AI)
Source	Benchmark	Score
Artificial Analysis	GLM-5.3 (Max) Intelligence Index	31.7
Artificial Analysis	GLM-5.3 (Max) Coding Index	74.8
Artificial Analysis	GLM-5.3 (Max) Agentic Index	53.1
Artificial Analysis	GLM-5.3 (Max) GPQA Diamond	91.7%
Artificial Analysis	GLM-5.3 (Max) HLE	42.3%
Artificial Analysis	GLM-5.3 (Max) AA-LCR	79.7%
Artificial Analysis	GLM-5.3 (Max) τ-Bench Banking	50.3%
Artificial Analysis	GLM-5.3 (Max) GDPval-AA	57.7%
Artificial Analysis	GLM-5.3 (Max) CritPt	19.1%
Artificial Analysis	GLM-5.3 (Max) SciCode	59.0%
Artificial Analysis	GLM-5.3 (Max) Terminal-Bench 4.0	41.9%
Artificial Analysis	GLM-5.3 (Max) Terminal-Bench 2.1	83.9%
Artificial Analysis	GLM-5.3 (Max) AA-Omniscience Accuracy	32.3%
Artificial Analysis	GLM-5.3 (Max) AA-Omniscience Non-Hallucination Rate	61.1%
Artificial Analysis	GLM-5.3 (Low) Intelligence Index	23.1
Artificial Analysis	GLM-5.3 (Low) HLE	36.6%
Artificial Analysis	GLM-5.3 (Low) AA-LCR	72.7%
Artificial Analysis	GLM-5.3 (Low) GDPval-AA	41.6%
Artificial Analysis	GLM-5.3 (Low) CritPt	14.6%
Artificial Analysis	GLM-5.3 (Low) SciCode	42.0%
Artificial Analysis	GLM-5.3 (Low) Terminal-Bench 4.0	34.8%
Artificial Analysis	GLM-5.3 (Low) AA-Omniscience Accuracy	31.9%
Artificial Analysis	GLM-5.3 (Low) AA-Omniscience Non-Hallucination Rate	36.8%
Design Arena	GLM-5.3 Models Arena 3D Elo	1295
Design Arena	GLM-5.3 Models Arena Asciiart Elo	1208
Design Arena	GLM-5.3 Models Arena Code Categories Elo	1284
Design Arena	GLM-5.3 Models Arena Data Visualization Elo	1251
Design Arena	GLM-5.3 Models Arena Game Development Elo	1288
Design Arena	GLM-5.3 Models Arena SVG Elo	1246
Design Arena	GLM-5.3 Models Arena UI Component Elo	1285
Design Arena	GLM-5.3 Models Arena Website Elo	1279
Design Arena	GLM-5.3 Agents Arena Htmlslides Elo	1189
Design Arena	GLM-5.3 Agents Arena Mobile Apps Elo	1184
Design Arena	GLM-5.3 Agents Arena Python-Pptxslides Elo	1216
Design Arena	GLM-5.3 Agents Arena Webapps Elo	1270
Vals AI	GLM 5.3 Access to Justice Benchmark	73.7%
Vals AI	GLM 5.3 Code Migration v1.1	55.1%
Vals AI	GLM 5.3 CyberBench v1.1	72.1%
Vals AI	GLM 5.3 EMB v1.1	69.1%
Vals AI	GLM 5.3 Finance Agent v2.1	65.0%
Vals AI	GLM 5.3 Vals Finance Index	61.4%
Vals AI	GLM 5.3 Financial Coaching Bench	74.1%
Vals AI	GLM 5.3 GPQA Diamond	88.1%
Vals AI	GLM 5.3 HLAB-Vals-1.1	14.6%
Vals AI	GLM 5.3 Immigration	66.7%
Vals AI	GLM 5.3 IOI	68.4%
Vals AI	GLM 5.3 LiveCodeBench	80.5%
Vals AI	GLM 5.3 LegalBench	84.8%
Vals AI	GLM 5.3 Vals Legal Index	74.6%
Vals AI	GLM 5.3 Legal Research Bench	49.0%
Vals AI	GLM 5.3 MedCode	42.9%
Vals AI	GLM 5.3 MedScribe	88.8%
Vals AI	GLM 5.3 MMLU Pro	86.8%
Vals AI	GLM 5.3 MysteryMechanism	23.0%
Vals AI	GLM 5.3 ProgramBench	1.5%
Vals AI	GLM 5.3 ProofBench v1.1	49.0%
Vals AI	GLM 5.3 Public Benefits Bench v1.1	68.5%
Vals AI	GLM 5.3 Vals RSI Index	22.9%
Vals AI	GLM 5.3 SkillsBench	47.5%
Vals AI	GLM 5.3 SRE Bench	9.2%
Vals AI	GLM 5.3 SWE-bench	95.4%
Vals AI	GLM 5.3 Tax Agent Bench	43.3%
Vals AI	GLM 5.3 TaxEval v2	72.4%
Vals AI	GLM 5.3 Terminal-Bench 4.0	38.9%
Vals AI	GLM 5.3 Terminal-Bench-Science	5.7%
Vals AI	GLM 5.3 Vals Index	59.8%
Vals AI	GLM 5.3 Vibe Code Bench 1-100 v1.1	29.8%
Vals AI	GLM 5.3 Vibe Code Bench v1.1	78.1%

Z.ai: GLM versions

Not currently available through EU in-region routing. In-region routing docs

More models from Z.ai

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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.

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GLM 5.3 Flash (batch)

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GLM 5.3 (batch)

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Z.ai: GLM 5.3 (batch)

Providers

Pricing

Weighted average

GLM 5.3 (batch) — Price history

Performance

Uptime

Benchmarks

Apps

Activity

API

Documentation

Frequently asked questions

Explore more models

More models from Z.ai

More models from Z.ai

Z.ai: GLM 5.3 (batch)

Providers

Pricing

Weighted average

GLM 5.3 (batch) — Price history

Performance

Uptime

Benchmarks

Apps

Activity

API

Documentation

Frequently asked questions

What is GLM 5.3 (batch)?

Where is the GLM 5.3 (batch) documentation?

How much does GLM 5.3 (batch) cost?

What is the context length of GLM 5.3 (batch)?

Does GLM 5.3 (batch) support tool calling and structured outputs?

Which providers serve GLM 5.3 (batch)?

When was GLM 5.3 (batch) released?

Explore more models

More models from Z.ai

More models from Z.ai