glm-4.7

glm-4.7

37.7K Downloads Updated 1 month ago

Advancing the Coding Capability

tools thinking cloud

ollama run glm-4.7:cloud

curl http://localhost:11434/api/chat \
  -d '{
    "model": "glm-4.7:cloud",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='glm-4.7:cloud',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'glm-4.7:cloud',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Applications

Claude Code

Claude Code ollama launch claude --model glm-4.7:cloud

Codex

Codex ollama launch codex --model glm-4.7:cloud

OpenCode

OpenCode ollama launch opencode --model glm-4.7:cloud

OpenClaw

OpenClaw ollama launch openclaw --model glm-4.7:cloud

Models

Name

1 model

Size

Context

Input

glm-4.7:cloud

198K context window · Text · 1 month ago

glm-4.7:cloud

-

198K

Text

Readme

GLM-4.7, your new coding partner, is coming with the following features:

Core Coding: GLM-4.7 brings clear gains, compared to its predecessor GLM-4.6, in multilingual agentic coding and terminal-based tasks, including (73.8%, +5.8%) on SWE-bench, (66.7%, +12.9%) on SWE-bench Multilingual, and (41%, +16.5%) on Terminal Bench 2.0. GLM-4.7 also supports thinking before acting, with significant improvements on complex tasks in mainstream agent frameworks such as Claude Code, Kilo Code, Cline, and Roo Code.
Vibe Coding: GLM-4.7 takes a major step forward in UI quality. It produces cleaner, more modern webpages and generates better-looking slides with more accurate layout and sizing.
Tool Using: GLM-4.7 achieves significantly improvements in Tool using. Significant better performances can be seen on benchmarks such as τ^2-Bench and on web browsing via BrowseComp.
Complex Reasoning: GLM-4.7 delivers a substantial boost in mathematical and reasoning capabilities, achieving (42.8%, +12.4%) on the HLE (Humanity’s Last Exam) benchmark compared to GLM-4.6.

You can also see significant improvements in many other scenarios such as chat, creative writing, and role-play scenario.

Benchmark Performance. More detailed comparisons of GLM-4.7 with other models GPT-5, GPT-5.1-High, Claude Sonnet 4.5, Gemini 3.0 Pro, DeepSeek-V3.2, Kimi K2 Thinking, on 17 benchmarks (including 8 reasoning, 5 coding, and 3 agents benchmarks) can be seen in the below table.

Coding: AGI is a long journey, and benchmarks are only one way to evaluate performance. While the metrics provide necessary checkpoints, the most important thing is still how it feels. True intelligence isn’t just about acing a test or processing data faster; ultimately, the success of AGI will be measured by how seamlessly it integrates into our lives-“coding” this time.

**GLM-4.7**, your new coding partner, is coming with the following features:

- **Core Coding:** GLM-4.7 brings clear gains, compared to its predecessor GLM-4.6, in multilingual agentic coding and terminal-based tasks, including (73.8%, +5.8%) on SWE-bench, (66.7%, +12.9%) on SWE-bench Multilingual, and (41%, +16.5%) on Terminal Bench 2.0. GLM-4.7 also supports thinking before acting, with significant improvements on complex tasks in mainstream agent frameworks such as Claude Code, Kilo Code, Cline, and Roo Code.
- **Vibe Coding:** GLM-4.7 takes a major step forward in UI quality. It produces cleaner, more modern webpages and generates better-looking slides with more accurate layout and sizing.
- **Tool Using:** GLM-4.7 achieves significantly improvements in Tool using. Significant better performances can be seen on benchmarks such as τ^2-Bench and on web browsing via BrowseComp.
- **Complex Reasoning:** GLM-4.7 delivers a substantial boost in mathematical and reasoning capabilities, achieving (42.8%, +12.4%) on the HLE (Humanity’s Last Exam) benchmark compared to GLM-4.6.

You can also see significant improvements in many other scenarios such as chat, creative writing, and role-play scenario.

![image.png](/assets/library/glm-4.7/668b8777-c7c9-4786-9370-d440c6195c6f)

**Benchmark Performance.** More detailed comparisons of GLM-4.7 with other models GPT-5, GPT-5.1-High, Claude Sonnet 4.5, Gemini 3.0 Pro, DeepSeek-V3.2, Kimi K2 Thinking, on 17 benchmarks (including 8 reasoning, 5 coding, and 3 agents benchmarks) can be seen in the below table.

![Ollama screenshot 2025-12-22 at 15.10.19@2x.png](/assets/library/glm-4.7/03e4b9bf-a7c8-471f-818b-aa7b15d4bc10)

**Coding:** AGI is a long journey, and benchmarks are only one way to evaluate performance. While the metrics provide necessary checkpoints, the most important thing is still how it *feels*. True intelligence isn't just about acing a test or processing data faster; ultimately, the success of AGI will be measured by how seamlessly it integrates into our lives-"coding" this time.

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