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GLM 4.1V Thinking FlashX

Added Jul 9, 2025

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Use in the app

Enhanced version of GLM 4.1V Thinking Flash. Vision-Language Model with advanced reasoning for complex visual tasks, multimodal problem solving, and intelligent agents. Supports 64k context length and handles arbitrary aspect ratios up to 4K resolution.

  • Vision
Input
Text, Images
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.30
Output
$0.30

Reference prices as published by the model provider. API example

Specifications

Context window
64K
Max output
8.2K

Side by side

GLM 4.1V Thinking FlashX compared

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

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GLM 4.1V Thinking FlashXZ.aiThis modelGLM 5.3 Flash TEEZ.aiRemove
ProviderZ.aiZ.ai
Discovery tierBalancedOpen weights
AddedJul 9, 2025Aug 28, 2026
Limits
Context window64K1.05MBest
Max output8.19K131.07KBest
Average output—845 tokens
Pricing, USD per 1M tokens
Input$0.30$0.15Best
Output$0.30Best$0.50
Cache read—$0.03
Performance
Throughput—345.2 tok/s
Time to first token—4.3 s
Request success (24h)—99.9%
Benchmark indexes
Intelligence Index—41.8
Coding Index—71.5
Capabilities
ReasoningNoYes
ToolsNoYes
VisionYesYes
Structured outputNoYes
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 4.1V Thinking FlashX
  • GLM 5.3 Flash TEE

Intelligence Index

  • GLM 4.1V Thinking FlashX—
  • GLM 5.3 Flash TEE41.8
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 71.5

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 60.4%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 25.4%

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 0.8%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 1,452 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 1,642 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 15.4%

  • AA-LCRv1.1

    Reasoning across long documents

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 80.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 11.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 39.9%

  • GPQA Diamond

    Graduate-level science questions

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 91.2%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 32.8%

  • SciCode

    Scientific computing in Python

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 51.6%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GLM 4.1V Thinking FlashX: —
    • GLM 5.3 Flash TEE: 80.0%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

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": "glm-4.1v-thinking-flashx",
    "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="glm-4.1v-thinking-flashx",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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