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Z.ai · Open weights

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 modelGemini 2.5 Flash Lite Preview (09/2025) – ThinkingGoogleRemove
ProviderZ.aiGoogle
Discovery tierOpen weightsEfficient
AddedJan 19, 2026Sep 25, 2025
Limits
Context window200K1.05MBest
Max output128KBest65.54K
Average output86 tokens—
Pricing, USD per 1M tokens
Input$0.07Best$0.10
Output$0.40Best$0.40
Cache read$0.01$0.01
Performance
Throughput28.7 tok/s—
Time to first token2.5 s—
Request success (24h)100.0%Best72.1%
Benchmark indexes
Intelligence Index10.6Best10.4
Math Index—68.7
Capabilities
ReasoningYesYes
ToolsYesYes
VisionNoYes
Structured outputYesYes
PDF inputNoYes
Audio inputNoYes
Reasoning effort—low, medium, high

Public evaluations

Benchmarks

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

  • GLM 4.7 Flash
  • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking

Intelligence Index

  • GLM 4.7 Flash10.6
  • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking10.4

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

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • GLM 4.7 Flash: —
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 68.7

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.7 Flash: 20.3%
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 64.7%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.7 Flash: 5.0%
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 7.0%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.7 Flash: 45.2%
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 70.9%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 4.7 Flash: —
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 80.8%

  • IFBench

    Following precise output instructions

    • GLM 4.7 Flash: 46.3%
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 52.6%Top

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 4.7 Flash: —
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 68.8%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 4.7 Flash: —
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 68.7%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 4.7 Flash: 3.8%
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 12.9%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 4.7 Flash: 91.8%Top
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 30.7%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.7 Flash: 20.3%
    • Gemini 2.5 Flash Lite Preview (09/2025) – Thinking: 64.7%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
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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