Z.ai · Open weights
GLM 4.7 Flash
GLM-4.7-Flash is a lightweight 30B model optimized for coding and agentic tasks. Balances high performance with efficiency.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.07
- Output
- $0.40
- Cache read
- $0.01
Reference prices as published by the model provider. API example
Specifications
- Context window
- 200K
- Max output
- 128K
- Average output (7 days)
- 86 tokens
- Longer than 8% of 468 models
Side by side
GLM 4.7 Flash compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 4.7 FlashZ.aiThis model | GLM 4.1V Thinking FlashZ.aiRemove | |
|---|---|---|
| Provider | Z.ai | Z.ai |
| Discovery tier | Open weights | Efficient |
| Added | Jan 19, 2026 | Jul 9, 2025 |
| Limits | ||
| Context window | 200KBest | 64K |
| Max output | 128KBest | 8.19K |
| Average output | 86 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.07Best | $0.30 |
| Output | $0.40 | $0.30Best |
| Cache read | $0.01 | — |
| Performance | ||
| Throughput | 28.7 tok/s | — |
| Time to first token | 2.5 s | — |
| Request success (24h) | 100.0% | — |
| Benchmark indexes | ||
| Intelligence Index | 10.6 | — |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | Yes | No |
| Vision | No | Yes |
| Structured output | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 4.7 Flash
- GLM 4.1V Thinking Flash
Intelligence Index
- GLM 4.7 Flash10.6
- GLM 4.1V Thinking Flash—
GLM 4.7 Flash: Better than 22% of 326 scored models
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- GLM 4.7 Flash: 20.3%
- GLM 4.1V Thinking Flash: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 4.7 Flash: 5.0%
- GLM 4.1V Thinking Flash: —
GPQA Diamond
Graduate-level science questions
- GLM 4.7 Flash: 45.2%
- GLM 4.1V Thinking Flash: —
IFBench
Following precise output instructions
- GLM 4.7 Flash: 46.3%
- GLM 4.1V Thinking Flash: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 4.7 Flash: 3.8%
- GLM 4.1V Thinking Flash: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 4.7 Flash: 91.8%
- GLM 4.1V Thinking Flash: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 4.7 Flash: 20.3%
- GLM 4.1V Thinking Flash: —
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 28.7 tok/s
- Faster than 20% of 253 models
- Time to first token
- 2.5 s
- Quicker than 64% of 253 models
- Prompt cache hits
- 14.7%
- About $0.0612 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "z-ai/glm-4.7-flash",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="z-ai/glm-4.7-flash",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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