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Z.ai · Open weights

GLM 5.3 Flash Uncensored

Added Jul 29, 2026Open weights

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Use in the app

GLM 5.3 Flash Uncensored is an uncensored fine-tune of the efficient 320B mixture-of-experts reasoning model with provider-dependent vision support, built for unrestricted chat, creative writing, coding, agentic work, tool use, and long-context tasks.

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

Pricing

USD per 1M tokens
Input
$0.20
Output
$0.80
Cache read
$0.07

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
32.8K
Average output (7 days)
692 tokens
Longer than 61% of 468 models

Side by side

GLM 5.3 Flash Uncensored 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 UncensoredZ.aiThis modelMinistral 14BMistralRemove
ProviderZ.aiMistral
Discovery tierOpen weightsOpen weights
AddedJul 29, 2026Dec 4, 2025
Limits
Context window1.05MBest262.14K
Max output32.77K32.77K
Average output692 tokens176 tokens
Pricing, USD per 1M tokens
Input$0.20$0.20
Output$0.80$0.20Best
Cache read$0.07—
Performance
Throughput212.0 tok/s—
Time to first token2.1 s—
Request success (24h)99.8%—
Benchmark indexes
Intelligence Index—6.0
Coding Index—14.4
Math Index—30.0
Capabilities
ReasoningYesNo
ToolsYesNo
VisionYesNo
Structured outputYesNo
Reasoning effortlow, high—

Public evaluations

Benchmarks

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

  • GLM 5.3 Flash Uncensored
  • Ministral 14B

Intelligence Index

  • GLM 5.3 Flash Uncensored—
  • Ministral 14B6.0
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 14.4

  • Math Index

    Composite of the math evaluations

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 30.0

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 0.6%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 0.2%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 131 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 247 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 1.2%

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 26.3%

  • MLCR-AA

    Long-context reasoning over medical records

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 2.2%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 4.6%

  • GPQA Diamond

    Graduate-level science questions

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 57.2%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 69.3%

  • IFBench

    Following precise output instructions

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 32.0%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 0.0%

  • SciCode

    Scientific computing in Python

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 23.8%

  • LiveCodeBench

    Recent competitive programming problems

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 35.1%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 30.0%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 4.5%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 27.2%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 5.3 Flash Uncensored: —
    • Ministral 14B: 26.3%

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
212.0 tok/s
Faster than 85% of 254 models
Time to first token
2.1 s
Quicker than 77% of 254 models
Prompt cache hits
92.7%
About $0.0795 per 1M input tokens with caching
Request success (24h)
99.8%
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 98.9%
  • 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": "z-ai/glm-5.3-flash-uncensored",
    "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="z-ai/glm-5.3-flash-uncensored",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Z.ai

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