Z.ai · Open weights
GLM 4.7 Original
GLM-4.7 is a next-gen GLM series text model with stronger reasoning, long-context chat, and reliable tool use. Routed directly via Z-AI (Zhipu).
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.40
- Output
- $1.93
- Cache read
- $0.0801
Reference prices as published by the model provider. API example
Specifications
- Context window
- 200K
- Max output
- 65.5K
- Average output (7 days)
- 562 tokens
- Longer than 53% of 468 models
Side by side
GLM 4.7 Original compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 4.7 OriginalZ.aiThis model | GLM 4.6 OriginalZ.aiRemove | |
|---|---|---|
| Provider | Z.ai | Z.ai |
| Discovery tier | Open weights | Open weights |
| Added | Dec 22, 2025 | Dec 11, 2025 |
| Limits | ||
| Context window | 200K | 256KBest |
| Max output | 65.54K | 65.54K |
| Average output | 562 tokens | 1.3K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.40Best | $0.50 |
| Output | $1.93Best | $2.00 |
| Cache read | $0.0801Best | $0.10 |
| Performance | ||
| Throughput | 78.1 tok/s | — |
| Time to first token | 2.8 s | — |
| Request success (24h) | 99.8%Best | 99.5% |
| Benchmark indexes | ||
| Intelligence Index | 17.4Best | 14.9 |
| Math Index | 48.0Best | 44.3 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | 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 Original
- GLM 4.6 Original
Intelligence Index
- GLM 4.7 Original17.4
- GLM 4.6 Original14.9
GLM 4.7 Original: Better than 46% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- GLM 4.7 Original: 48.0Top
- GLM 4.6 Original: 44.3
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- GLM 4.7 Original: 40.7%Top
- GLM 4.6 Original: 26.3%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 4.7 Original: 6.4%Top
- GLM 4.6 Original: 5.5%
GPQA Diamond
Graduate-level science questions
- GLM 4.7 Original: 66.4%Top
- GLM 4.6 Original: 63.2%
MMLU-Pro
Multi-subject knowledge and reasoning
- GLM 4.7 Original: 79.4%Top
- GLM 4.6 Original: 78.4%
IFBench
Following precise output instructions
- GLM 4.7 Original: 54.6%Top
- GLM 4.6 Original: 36.7%
Coding
LiveCodeBench
Recent competitive programming problems
- GLM 4.7 Original: 56.2%Top
- GLM 4.6 Original: 56.1%
Math
AIME 2025
Competition mathematics, 2025 problems
- GLM 4.7 Original: 48.0%Top
- GLM 4.6 Original: 44.3%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 4.7 Original: 30.3%Top
- GLM 4.6 Original: 28.8%
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 4.7 Original: 94.2%Top
- GLM 4.6 Original: 76.9%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 4.7 Original: 40.7%Top
- GLM 4.6 Original: 26.3%
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
- 78.1 tok/s
- Faster than 52% of 258 models
- Time to first token
- 2.8 s
- Quicker than 60% of 258 models
- Prompt cache hits
- 56.4%
- About $0.22 per 1M input tokens with caching
- Request success (24h)
- 99.8%
- 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-original",
"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-original",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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