Z.ai · Open weights
GLM 4.7 Flash Thinking
GLM-4.7-Flash with extended thinking capabilities for complex reasoning. Lightweight 30B model optimized for coding and agentic tasks.
- Reasoning
- Tools
- 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)
- 2.3K tokens
- Longer than 93% of 468 models
Side by side
GLM 4.7 Flash Thinking compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GLM 4.7 Flash ThinkingZ.aiThis model | Gemma 4 31B IT TEEGoogleRemove | |
|---|---|---|
| Provider | Z.ai | |
| Discovery tier | Open weights | Open weights |
| Added | Jan 19, 2026 | May 26, 2026 |
| Limits | ||
| Context window | 200K | 262.14KBest |
| Max output | 128K | 262.14KBest |
| Average output | 2.3K tokens | 269 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.07Best | $0.15 |
| Output | $0.40Best | $0.46 |
| Cache read | $0.01 | — |
| Performance | ||
| Throughput | 43.1 tok/s | 62.7 tok/sBest |
| Time to first token | 6.6 s | 3.9 sBest |
| Request success (24h) | 100.0%Best | 99.8% |
| Benchmark indexes | ||
| Intelligence Index | 14.9Best | 14.7 |
| Coding Index | — | 43.4 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GLM 4.7 Flash Thinking
- Gemma 4 31B IT TEE
Intelligence Index
- GLM 4.7 Flash Thinking14.9
- Gemma 4 31B IT TEE14.7
GLM 4.7 Flash Thinking: Better than 37% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 43.4
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 4.9%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 0.5%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 368 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 619 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 6.0%
AA-LCRv1.1
Reasoning across long documents
- GLM 4.7 Flash Thinking: 41.7%
- Gemma 4 31B IT TEE: 69.7%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GLM 4.7 Flash Thinking: 7.6%
- Gemma 4 31B IT TEE: 23.6%Top
GPQA Diamond
Graduate-level science questions
- GLM 4.7 Flash Thinking: 58.1%
- Gemma 4 31B IT TEE: 85.7%Top
IFBench
Following precise output instructions
- GLM 4.7 Flash Thinking: 60.8%
- Gemma 4 31B IT TEE: 75.6%Top
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 0.0%
SciCode
Scientific computing in Python
- GLM 4.7 Flash Thinking: —
- Gemma 4 31B IT TEE: 45.5%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GLM 4.7 Flash Thinking: 22.0%
- Gemma 4 31B IT TEE: 36.4%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- GLM 4.7 Flash Thinking: 98.8%Top
- Gemma 4 31B IT TEE: 59.9%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GLM 4.7 Flash Thinking: 41.7%
- Gemma 4 31B IT TEE: 69.7%Top
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
- 43.1 tok/s
- Faster than 31% of 254 models
- Time to first token
- 6.6 s
- Quicker than 25% of 254 models
- Prompt cache hits
- 0.0%
- About $0.07 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:thinking",
"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:thinking",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Z.ai
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