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GLM 4.7 Flash

Added Jan 19, 2026Open weights

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Use in the app

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.

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GLM 4.7 FlashZ.aiThis modelGLM 5.3 Flash TEEZ.aiRemove
ProviderZ.aiZ.ai
Discovery tierOpen weightsOpen weights
AddedJan 19, 2026Aug 28, 2026
Limits
Context window200K1.05MBest
Max output128K131.07KBest
Average output86 tokens845 tokens
Pricing, USD per 1M tokens
Input$0.07Best$0.15
Output$0.40Best$0.50
Cache read$0.01Best$0.03
Performance
Throughput28.7 tok/s75.4 tok/sBest
Time to first token2.5 sBest3.8 s
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index10.641.8Best
Coding Index—71.5
Capabilities
ReasoningYesYes
ToolsYesYes
VisionNoYes
Structured outputYesYes
Parallel toolsNoYes
Reasoning effort—low, high, max

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • GLM 4.7 Flash
  • GLM 5.3 Flash TEE

Intelligence Index

  • GLM 4.7 Flash10.6
  • GLM 5.3 Flash TEE41.8

GLM 4.7 Flash: Better than 22% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 71.5

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 60.4%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 25.4%

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 0.8%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 1,452 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 1,642 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 15.4%

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.7 Flash: 20.3%
    • GLM 5.3 Flash TEE: 80.0%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 11.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.7 Flash: 5.0%
    • GLM 5.3 Flash TEE: 39.9%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.7 Flash: 45.2%
    • GLM 5.3 Flash TEE: 91.2%Top

  • IFBench

    Following precise output instructions

    • GLM 4.7 Flash: 46.3%
    • GLM 5.3 Flash TEE: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 32.8%

  • SciCode

    Scientific computing in Python

    • GLM 4.7 Flash: —
    • GLM 5.3 Flash TEE: 51.6%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 4.7 Flash: 3.8%
    • GLM 5.3 Flash TEE: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 4.7 Flash: 91.8%
    • GLM 5.3 Flash TEE: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.7 Flash: 20.3%
    • GLM 5.3 Flash TEE: 80.0%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
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.

Hourly request success · last 72 hoursLowest hour 98.2%
  • 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.

Read the quickstart
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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