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GLM 5.3 Flash TEE

Added Aug 28, 2026Open weights

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GLM-5.3 Flash is Z.AI's natively multimodal 320B MoE reasoning model with 18B active parameters. This TEE deployment is verified through Redpill attestation with signed completion receipts.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Parallel tools
Input
Text, Images
Output
Text
Reasoning effort
low · high · max
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.15
Output
$0.50
Cache read
$0.03

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
131.1K
Average output (7 days)
845 tokens
Longer than 66% of 465 models

Side by side

GLM 5.3 Flash TEE compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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GLM 5.3 Flash TEEZ.aiThis modelGLM 4.7 FlashZ.aiRemove
ProviderZ.aiZ.ai
Discovery tierOpen weightsOpen weights
AddedAug 28, 2026Jan 19, 2026
Limits
Context window1.05MBest200K
Max output131.07KBest128K
Average output845 tokens86 tokens
Pricing, USD per 1M tokens
Input$0.15$0.07Best
Output$0.50$0.40Best
Cache read$0.03$0.01Best
Performance
Throughput75.4 tok/sBest51.4 tok/s
Time to first token3.8 sBest3.8 s
Request success (24h)99.9%100.0%Best
Benchmark indexes
Intelligence Index41.8Best10.6
Coding Index71.5—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesNo
Structured outputYesYes
Parallel toolsYesNo
Reasoning effortlow, high, max—

Public evaluations

Benchmarks

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

  • GLM 5.3 Flash TEE
  • GLM 4.7 Flash

Intelligence Index

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

GLM 5.3 Flash TEE: Better than 86% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

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

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

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

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

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

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

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

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

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

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

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

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

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

  • AA-LCRv1.1

    Reasoning across long documents

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

  • MLCR-AA

    Long-context reasoning over medical records

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

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

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

  • GPQA Diamond

    Graduate-level science questions

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

  • IFBench

    Following precise output instructions

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

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

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

  • SciCode

    Scientific computing in Python

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

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

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

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

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

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

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

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
75.4 tok/s
Faster than 51% of 250 models
Time to first token
3.8 s
Quicker than 48% of 250 models
Prompt cache hits
95.9%
About $0.0349 per 1M input tokens with caching
Request success (24h)
99.9%
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 52.9%
  • 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": "TEE/glm-5.3-flash",
    "reasoning_effort": "low",
    "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="TEE/glm-5.3-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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