glm-4.7-flash:bf16

625 Downloads Updated 8 hours ago

As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency.

tools thinking

ollama run glm-4.7-flash:bf16

curl http://localhost:11434/api/chat \
  -d '{
    "model": "glm-4.7-flash:bf16",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='glm-4.7-flash:bf16',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'glm-4.7-flash:bf16',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Details

Updated 8 hours ago

8 hours ago

e7e66b0733eb · 60GB ·

model

archglm4moelite

parameters29.9B

quantizationF16

60GB

params

{ "temperature": 1 }

18B

Readme

Note: this model requires Ollama 0.14.3 which is currently in pre-release.

Introduction

GLM-4.7-Flash is a 30B-A3B MoE model. As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency.

Performances on Benchmarks

Benchmark	GLM-4.7-Flash	Qwen3-30B-A3B-Thinking-2507	GPT-OSS-20B
AIME 25	91.6	85.0	91.7
GPQA	75.2	73.4	71.5
LCB v6	64.0	66.0	61.0
HLE	14.4	9.8	10.9
SWE-bench Verified	59.2	22.0	34.0
τ²-Bench	79.5	49.0	47.7
BrowseComp	42.8	2.29	28.3

> Note: this model requires [Ollama 0.14.3](https://github.com/ollama/ollama/releases) which is currently in pre-release.

## Introduction

GLM-4.7-Flash is a 30B-A3B MoE model. As the strongest model in the 30B class, GLM-4.7-Flash offers a new option for lightweight deployment that balances performance and efficiency.

### Performances on Benchmarks

| Benchmark          | GLM-4.7-Flash | Qwen3-30B-A3B-Thinking-2507 | GPT-OSS-20B |
|--------------------|---------------|-----------------------------|-------------|
| AIME 25            | 91.6          | 85.0                        | 91.7        |
| GPQA               | 75.2          | 73.4                        | 71.5        |
| LCB v6             | 64.0          | 66.0                        | 61.0        |
| HLE                | 14.4          | 9.8                         | 10.9        |
| SWE-bench Verified | 59.2          | 22.0                        | 34.0        |
| τ²-Bench           | 79.5          | 49.0                        | 47.7        |
| BrowseComp         | 42.8          | 2.29                        | 28.3        |

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