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GLM-5

Chat modelGLMGLM-5

GLM-5

Release date: 2026-02-11Updated: 2026-07-17Views: 9,681
Live demoGitHubHugging FaceCompare
Parameters
744B
Context length
200K
Multilingual
Supported
Reasoning ability
4/5

GLM-5 is a chat model from Zhipu AI, released on 2026-02-11. It accepts text input and returns text output. The cataloged parameter count is 744B, with 40B active parameters per inference. The recorded context window is 200K, and the recorded maximum output is 128K. Cataloged capabilities include Reasoning model and Multilingual. The checkpoint is listed under the MIT license, with the license link included in the model references. Use the linked references to confirm current access, licensing, and provider-specific limits.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

GLM-5

Model basics

Reasoning traces
Supported
Thinking modes
Standard ModeThinking Level · Extended
Context length
200K tokens
Max output length
128K tokens
Model type
Chat model
Modality (in / out)
Text → Text
Release date
2026-02-11
Model file size
1.51TB
MoE architecture
Yes
Total params / Active params
744B / 40B
Knowledge cutoff
No data
GLM-5

Open source & experience

Code license
Apache 2.0
Weights license
MIT License- Commercial use permitted
GitHub repo
github.com/zai-org/GLM-5
Hugging Face
huggingface.co/zai-org/GLM-5
Live demo
chat.z.ai
GLM-5

Official resources

Paper
Paper
DataLearnerAI blog
N/A
GLM-5

API details

API speed
3/5
💡Default unit: $/1M tokens. If vendors use other units, follow their published pricing.
Learn about pricing modes
Standard
TypeConditionInputOutput
Text-$1.00/ 1M$3.20/ 1M
Cache PricingPrompt Cache
TypeTTLWriteRead
Text5m$0.200/ 1M—

“—” means the modality is not billed in that direction, or the vendor has not published a price for it.

GLM-5

Benchmark Results

GLM-5 currently shows benchmark results led by τ²-Bench (4 / 44, score 89.70), τ²-Bench - Telecom (5 / 36, score 98), Terminal Bench Hard (2 / 13, score 43). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.

Thinking
Tool usage

General Knowledge

5 evaluations
Benchmark / mode
Score
Rank/total
LiveBench
Standard Mode
68.85
43 / 117
HLE
Thinking Mode
30.50
106 / 197
HLE
Thinking ModeTools
50.40
34 / 197
ARC-AGI-1
Thinking Mode
44.70
71 / 92
ARC-AGI-2
Thinking Mode
4.90
70 / 85

General Evaluation

1 evaluations
Benchmark / mode
Score
Rank/total
GPQA Diamond
Thinking Mode
86
94 / 274

Coding and Software Engineer

1 evaluations
Benchmark / mode
Score
Rank/total
SWE-bench Verified
Thinking Mode
77.80
25 / 116

Writing and Creative Capabilities

1 evaluations
Benchmark / mode
Score
Rank/total
Creative Writing
Standard Mode
1597.50
39 / 106

Common Sense Reasoning

1 evaluations
Benchmark / mode
Score
Rank/total
SimpleBench
Standard Mode
53.20
45 / 94

Agent Level Benchmark

3 evaluations
Benchmark / mode
Score
Rank/total
τ²-Bench - Telecom
Thinking ModeTools
98
5 / 36
τ²-Bench
Thinking ModeTools
89.70
4 / 44
Terminal Bench Hard
Thinking ModeTools
43
2 / 13

Math and Reasoning

3 evaluations
Benchmark / mode
Score
Rank/total
AIME 2026
Thinking Mode
92.70
10 / 21
IMO-AnswerBench
Thinking Mode
82.50
17 / 24
FrontierMath - Tier 4
Standard Mode
2.10
56 / 80

Instruction Following

1 evaluations
Benchmark / mode
Score
Rank/total
IF Bench
Thinking ModeTools
72
15 / 36

AI Agent - Information Search

2 evaluations
Benchmark / mode
Score
Rank/total
BrowseComp
Thinking Mode
62
35 / 57
BrowseComp
Thinking ModeTools
75.90
26 / 57

AI Agent - Tool Usage

1 evaluations
Benchmark / mode
Score
Rank/total
Terminal Bench 2.0
Thinking ModeTools
61.10
18 / 48

Productivity Knowledge

1 evaluations
Benchmark / mode
Score
Rank/total
GDPval-AA
Thinking Mode
46
14 / 21

Long Context

2 evaluations
Benchmark / mode
Score
Rank/total
AA-LCR
Thinking Mode
63
24 / 29
LongBench v2
Standard Mode
60.80
7 / 14

Claw-style Agent Evaluation

2 evaluations
Benchmark / mode
Score
Rank/total
Claw Bench
Thinking ModeTools
91.70
5 / 29
Pinch Bench
Thinking ModeTools
86.40
13 / 38
View benchmark analysisCompare with other models

Compare with other models

GLM-5

Publisher

GLM-5

Model Overview

GLM-5 is a chat model from Zhipu AI, released on 2026-02-11.

It accepts text input and produces text output. Its cataloged capabilities include Reasoning model and Multilingual. The cataloged parameter count is 744B, with 40B active parameters per inference. The recorded context window is 200K, and the recorded maximum output is 128K.

The checkpoint is listed under the MIT license, with the license link included in the model references. The page records 3 API pricing rules from the listed provider; current provider pricing and conditions should be checked before deployment. The evaluation section contains 23 cataloged benchmark results with their recorded modes and scores. The page links 4 release, model-card, repository, or provider references for checking the underlying claims. Specifications, availability, and prices can change; undisclosed values are intentionally left unstated.

GLM-5

FAQ

What is GLM-5?

GLM-5 is a chat model from Zhipu AI, released on 2026-02-11. It accepts text input and returns text output. The cataloged parameter count is 744B, with 40B active parameters per inference. The recorded context window is 200K, and the recorded maximum output is 128K. Cataloged capabilities include Reasoning model and Multilingual. The checkpoint is listed under the MIT license, with the license link included in the model references. Use the linked references to confirm current access, licensing, and provider-specific limits.

What input and output modalities does GLM-5 support?

The current model record lists text as input and text as output.

What are the main recorded specifications for GLM-5?

The cataloged parameter count is 744B, with 40B active parameters per inference. The recorded context window is 200K, and the recorded maximum output is 128K. Fields without a source-backed value remain undisclosed.

Does GLM-5 have API pricing?

The page records 3 API pricing rules from the listed provider; current provider pricing and conditions should be checked before deployment.

Are benchmark results available for GLM-5?

The evaluation section contains 23 cataloged benchmark results with their recorded modes and scores. Compare only results that use the same benchmark version and evaluation mode.

Is GLM-5 open source?

The checkpoint is listed under the MIT license, with the license link included in the model references. Review the linked license text before commercial or derivative use.

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