GLM-5.3 (max) Intelligence, Performance & Price Analysis

Artificial Analysis

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GLM-5.3 (max) logo

Z AI

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Proprietary model

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Released August 2026

GLM-5.3 (max) Intelligence, Performance & Price Analysis

CompareAPI Provider Benchmarks

Model summary

#### Intelligence

#8 / 182

Artificial Analysis Intelligence Index

4 out of 4 units for Intelligence.

#### Speed

#55 / 182

93.2

Output tokens per second

3 out of 4 units for Speed.

#### Cost

#54 / 182

In $1.40Out $4.40Cache Discount 81%

$0.68

Cost per Intelligence Index task

3 out of 4 units for Cost.

#### Verbosity

#73 / 182

170M

Output tokens from Intelligence Index

4 out of 4 units for Verbosity.

Comparison Summary

GLM-5.3 (max) is amongst the leading models in intelligence and reasonably priced when comparing to other models of similar price. It's also faster than average, however very verbose. The model supports text input, outputs text, and has a 1M tokens context window.

GLM-5.3 (max) scores 60 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 35). When evaluating the Intelligence Index, it generated 170M tokens, which is very verbose in comparison to the median of 72M.

Pricing for GLM-5.3 (max) is $1.40 per 1M input tokens (moderately priced, median: $1.75) and $4.40 per 1M output tokens (moderately priced, median: $10.00). In total, it cost $1238.50 to evaluate GLM-5.3 (max) on the Intelligence Index.

At 93 tokens per second, GLM-5.3 (max) is faster than average (75).

Technical specifications

| Reasoning | YesThis page shows the reasoning version of this model.A non-reasoning variant may also exist. | | --------------- | ---------------------------------------------------------------------------------------------- | | Input modality | Supports: text | | Output modality | Supports: text | | Context window | 1M\~1500 A4 pages of size 12 Arial font |

182 models in this class

Metrics are compared against models of the same class:

Non-reasoning models → compared only with other non-reasoning models
Reasoning models → compared across both reasoning and non-reasoning
Open weights models → compared only with other open weights models of the same size class:
Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:

Highlights

Intelligence

Artificial Analysis Intelligence Index · Higher is better

Speed

Output tokens per second · Higher is better

Cost per Task

Weighted average cost (USD) per Intelligence Index task · Lower is better

Prompt Options

Intelligence

Artificial Analysis Intelligence IndexUpdatedAgentic IndexUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR

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Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Open Weights / ProprietaryReasoning / Non-ReasoningText Only / Multimodal Inputs

Artificial Analysis Intelligence Index by Open Weights / Proprietary

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ProprietaryOpen Weights (Commercial Use Restricted)Open Weights

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Artificial Analysis Intelligence Index

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Open Weights

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

Benchmarks

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

CodingTool UsePrivate DatasetUser InteractionFinanceMedicalLegalIntelligence IndexLong ContextMultimodalInstruction FollowingFaithfulnessWritingBusinessSee more

19 of 23 evaluations

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GDPval-AA v2

Agentic real-world work tasks, (Elo-500)/2000

𝜏³-BankingUpdated

Agentic tool use

Terminal-Bench v2.1

Agentic coding & terminal use

SciCode

Coding

Humanity's Last ExamUpdated

Reasoning & knowledge

GPQA Diamond

Scientific reasoning

CritPt

Physics reasoning

AA-Omniscience AccuracyUpdated

Knowledge

AA-Omniscience Non-Hallucination RateUpdated

1 - hallucination rate

AA-LCRUpdated

Long context reasoning

AA-Briefcase

Agentic knowledge work, Elo

AutomationBench-AA

Agentic SaaS workflows

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AA

Agentic business operations

AA-AnalystAgentNew

Quantitative analysis on spreadsheets & documents

IFBench

Instruction following

APEX-Agents-AA

Long-horizon agentic tasks

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

Visual reasoning

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Intelligence Evaluation Relevance

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

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Artificial Analysis Intelligence Index

AA-Omniscience

AA-Omniscience IndexAA-Omniscience AccuracyAA-Omniscience Hallucination Rate

AA-Omniscience Index

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

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AA-Omniscience Index

Intelligence Index Comparisons

Intelligence Index vs. Cost per TaskIntelligence Index vs. Time per TaskIntelligence Index vs. Output SpeedIntelligence Index vs. End-to-End Response Time

Intelligence Index vs. Cost per Intelligence Index Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

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Most attractive quadrant

Pareto line

Z AIMetaOpenAINVIDIADeepSeekGoogleAnthropicSpaceXAIKimiAlibaba

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Cost per Intelligence Index Task

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

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Artificial Analysis Intelligence Index

Token Use

Output Tokens per TaskIntelligence Index vs. Output Tokens per TaskIntelligence Index Token UseIntelligence Index vs. Token Use

Output Tokens per Intelligence Index Task

Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index

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AnswerReasoning

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Output Tokens per Intelligence Index Task

The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats).

Cost

Cost per TaskIntelligence Index vs. Cost per TaskEvaluation Breakdown

Cost per Intelligence Index Task

Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better

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AnswerReasoningCache WriteCache HitInput

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Cost per Intelligence Index Task

Intelligence Index Total CostIntelligence Index vs. Total Cost

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index

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OutputReasoningCache WriteCache ReadNon-Cache Input

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Cost to Run Artificial Analysis Intelligence Index

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Cache Hit, Input, and Output PricingBlended PriceBlended Price (Stacked)Cache DiscountIntelligence Index vs. PriceIntelligence Index vs. Price (Log, Inverted)Image Input Pricing

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

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Cache HitInputOutput

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Cache Hit

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

4 more notes

Context Window

Context WindowIntelligence Index vs. Context Window

Context Window

Context window: tokens limit · Higher is better

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Context Window for RAG

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

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Context Window

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Speed

Measured by Output Speed (tokens per second)

Output SpeedOutput Speed by Prompt TypeOutput Speed VarianceOutput Speed Over TimeOutput Speed vs. PriceLatency vs. Output Speed

Output Speed

Output tokens per second · Higher is better

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Output Speed

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

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Model Performance Representation

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Time per TaskIntelligence Index vs. Time per TaskCost vs. Time per Task

Time per Intelligence Index Task

Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better

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Time per Intelligence Index Task

The weighted average time (seconds) per Artificial Analysis Intelligence Index task. This is calculated by dividing output tokens per task by output speed, weighted by the relative weights of each benchmark in the Intelligence Index.

Latency

Measured by Time (seconds) to First Token

Time To First Answer TokenTime To First TokenLatency by Prompt TypeLatency VarianceLatency Over Time

Latency: Time To First Answer Token

Seconds to first answer token received · Accounts for reasoning model 'thinking' time

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Thinking (reasoning models, when applicable)Input processing

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Time to First Answer Token

Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.

End-to-End Response Time

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response TimeEnd-to-End Response Time by Prompt TypeEnd-to-End Response Time Over Time

End-to-End Response Time

Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better

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Outputting time'Thinking' time (reasoning models)Input processing time

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End-to-End Response Time

Seconds to receive a 500 token response. Key components:

Input time: Time to receive the first response token
Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
Answer time: Time to generate 500 output tokens, based on output speed

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Model Performance Representation

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Frequently Asked Questions

Common questions about GLM-5.3 (max)

When was GLM-5.3 (max) released?

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

Who created GLM-5.3 (max)?

GLM-5.3 (max) was created by Z AI.

How intelligent is GLM-5.3 (max)?

GLM-5.3 (max) scores 60 on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 35).

How fast is GLM-5.3 (max)?

GLM-5.3 (max) generates output at 93.2 tokens per second (based on Z AI's API), which is above average compared to other reasoning models in a similar price tier (median: 75.4 t/s).

What is the latency of GLM-5.3 (max)?

GLM-5.3 (max) has a time to first token (TTFT) of 1.92s (based on Z AI's API), which is better than average compared to other reasoning models in a similar price tier (median: 2.81s).

How much does GLM-5.3 (max) cost?

GLM-5.3 (max) costs $1.40 per 1M input tokens (better than average, median: $1.75) and $4.40 per 1M output tokens (better than average, median: $10.00), based on Z AI's API.

What is GLM-5.3 (max) API pricing?

GLM-5.3 (max) costs $1.40 per 1M input tokens and $4.40 per 1M output tokens (based on Z AI's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.90 per 1M tokens. Pricing may vary by provider. Compare provider pricing

How verbose is GLM-5.3 (max)?

When evaluated on the Intelligence Index, GLM-5.3 (max) generated 170M output tokens, which is at the higher end compared to other reasoning models in a similar price tier (median: 72M).

Is GLM-5.3 (max) a reasoning model?

Yes, GLM-5.3 (max) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

What input modalities does GLM-5.3 (max) support?

GLM-5.3 (max) supports text input.

What output modalities does GLM-5.3 (max) support?

GLM-5.3 (max) supports text output.

Can GLM-5.3 (max) process images?

No, GLM-5.3 (max) does not support image input. It can only process text.

Is GLM-5.3 (max) multimodal?

No, GLM-5.3 (max) is not multimodal. It only supports text input.

What is the context window of GLM-5.3 (max)?

GLM-5.3 (max) has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request.

Is GLM-5.3 (max) open source?

No, GLM-5.3 (max) is proprietary. The model weights are not publicly available.

How many parameters does GLM-5.3 (max) have?

GLM-5.3 (max) has 753 billion parameters.

How does GLM-5.3 (max) perform on benchmarks?

GLM-5.3 (max) achieves a score of 60 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Is GLM-5.3 (max) available via API?

Yes, GLM-5.3 (max) is available via API through 2 providers. Compare API providers

Where can I use GLM-5.3 (max)?

GLM-5.3 (max) is available through 2 API providers. Compare providers

GLM-5.3 (max) Intelligence, Performance & Price Analysis

GLM-5.3 (max) Intelligence, Performance & Price Analysis

GLM-5.3 (max) Intelligence, Performance & Price Analysis

Model summary

Comparison Summary

Technical specifications

182 models in this class

Intelligence

Speed

Cost per Task

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Benchmarks

Intelligence Evaluations

AA-Omniscience

AA-Omniscience Index

Intelligence Index Comparisons

Intelligence Index vs. Cost per Intelligence Index Task

Token Use

Output Tokens per Intelligence Index Task

Cost

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Context Window

Context Window

Speed

Output Speed

Time per Intelligence Index Task

Latency

Latency: Time To First Answer Token

End-to-End Response Time

End-to-End Response Time

Frequently Asked Questions

When was GLM-5.3 (max) released?

Who created GLM-5.3 (max)?

How intelligent is GLM-5.3 (max)?

How fast is GLM-5.3 (max)?

What is the latency of GLM-5.3 (max)?

How much does GLM-5.3 (max) cost?

What is GLM-5.3 (max) API pricing?

How verbose is GLM-5.3 (max)?

Is GLM-5.3 (max) a reasoning model?

What input modalities does GLM-5.3 (max) support?

What output modalities does GLM-5.3 (max) support?

Can GLM-5.3 (max) process images?

Is GLM-5.3 (max) multimodal?

What is the context window of GLM-5.3 (max)?

Is GLM-5.3 (max) open source?

How many parameters does GLM-5.3 (max) have?

How does GLM-5.3 (max) perform on benchmarks?

Is GLM-5.3 (max) available via API?

Where can I use GLM-5.3 (max)?

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