Z.ai mit Released Jan 19, 2026 Updated
GLM-4.7-Flash
ToolsGuide Scores, rankings, test results and price.
Model summary
- Text #181 / 419
271 / 1,000
ToolsGuide Score· votes 239, tests 310
- Price per 1M tokens
No listed price
Summary
GLM-4.7-Flash is Z.ai's model, released Jan 19, 2026. It's ranked in 1 category and does best at text: #181 of 419, with a ToolsGuide Score of 271 against a median of 252.
It has published results on 6 tests.
Specifications
- Creator
Z.ai- Licence
- mit
- Released
- Jan 19, 2026
- Context window
- –
- Input price
- –
- Output price
- –
- Tests reported
- 6
- Settings ranked
- GLM-4.7-Flash
Model comparison
Against the ten best text models.
Text score
ToolsGuide Score out of 1,000 · Higher is better
Input price
USD per 1M input tokens · Lower is better
Leaderboards
Where GLM-4.7-Flash sits among the top 20 in each category.
Text
#181 of 419 · ToolsGuide Score out of 1,000, where 1,000 is a flawless model
By task
Scored from votes on each kind of prompt alone, on the same 1,000-point scale.
Against its nearest rivals
Text prompts by kind · ToolsGuide Score from votes · hover for values
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GLM-4.7-Flash -
Qwen3-Next-80B-A3B-Instruct
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o1-preview
Text
GLM-4.7-Flash · hover a bar for its rank
Test results
Every test GLM-4.7-Flash has a published result on, out of 100%, with its rank among the models that took it.
GPQA
#129 / 265Graduate-level science questions written to be hard to look up.
75.2%
Self-reported
AIME 2025
#43 / 124Competition maths problems from the 2025 American Invitational Mathematics Exam.
91.6%
Self-reported
SWE-Bench Verified
#96 / 123Fixing real bugs in real GitHub projects, checked by the projects' own tests.
59.2%
Self-reported
Humanity's Last Exam
#93 / 115Humanity's Last Exam (HLE) is a multi-modal academic benchmark with 2,500 questions across mathematics, humanities, and natural sciences, designed to test LLM capabilities at the frontier of human knowledge with unambiguous, verifiable solutions
14.4%
Self-reported · In the text score· In the vision score
BrowseComp
#65 / 73Finding hard-to-locate facts by browsing the web.
42.8%
Self-reported · In the agents score
Tau-bench
#4 / 6τ-bench: A benchmark for tool-agent-user interaction in real-world domains. Tests language agents' ability to interact with users and follow domain-specific rules through dynamic conversations using API tools and policy guidelines across retail and airline domains. Evaluates consistency and reliability of agent behavior over multiple trials.
79.5%
Self-reported