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GLM 5.3 Flash TEE

Added Aug 28, 2026Open weights

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Use in the app

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 modelClaude Opus 4.8AnthropicRemove
ProviderZ.aiAnthropic
Discovery tierOpen weightsFrontier
AddedAug 28, 2026May 28, 2026
Limits
Context window1.05MBest1M
Max output131.07KBest128K
Average output845 tokens360 tokens
Pricing, USD per 1M tokens
Input$0.15Best$5.00
Output$0.50Best$25.00
Cache read$0.03Best$0.50
Performance
Throughput75.4 tok/sBest72.6 tok/s
Time to first token3.8 s1.4 sBest
Request success (24h)99.9%100.0%Best
Benchmark indexes
Intelligence Index41.841.8
Coding Index71.574.3Best
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputNoYes
Parallel toolsYesNo
Reasoning effortlow, high, maxlow, medium, high, xhigh, max

Public evaluations

Benchmarks

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

  • GLM 5.3 Flash TEE
  • Claude Opus 4.8

Intelligence Index

  • GLM 5.3 Flash TEE41.8
  • Claude Opus 4.841.8

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
    • Claude Opus 4.8: 74.3Top

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 5.3 Flash TEE: 60.4%Top
    • Claude Opus 4.8: 45.6%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 5.3 Flash TEE: 25.4%Top
    • Claude Opus 4.8: 17.4%

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • GLM 5.3 Flash TEE: 0.8%
    • Claude Opus 4.8: —

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GLM 5.3 Flash TEE: 1,452 EloTop
    • Claude Opus 4.8: 1,319 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 5.3 Flash TEE: 1,642 EloTop
    • Claude Opus 4.8: 1,454 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 5.3 Flash TEE: 15.4%
    • Claude Opus 4.8: 22.8%Top

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 5.3 Flash TEE: 80.0%Top
    • Claude Opus 4.8: 77.7%

  • MLCR-AA

    Long-context reasoning over medical records

    • GLM 5.3 Flash TEE: 11.7%
    • Claude Opus 4.8: 19.4%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 5.3 Flash TEE: 39.9%
    • Claude Opus 4.8: 48.7%Top

  • GPQA Diamond

    Graduate-level science questions

    • GLM 5.3 Flash TEE: 91.2%
    • Claude Opus 4.8: 92.0%Top

  • IFBench

    Following precise output instructions

    • GLM 5.3 Flash TEE: —
    • Claude Opus 4.8: 62.2%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 5.3 Flash TEE: 32.8%Top
    • Claude Opus 4.8: 21.7%

  • SciCode

    Scientific computing in Python

    • GLM 5.3 Flash TEE: 51.6%
    • Claude Opus 4.8: 54.4%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 5.3 Flash TEE: —
    • Claude Opus 4.8: 58.3%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 5.3 Flash TEE: —
    • Claude Opus 4.8: 94.4%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 5.3 Flash TEE: 80.0%Top
    • Claude Opus 4.8: 77.7%

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

Other Z.ai models, starting with the same family.