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Qwen3 VL 235B A22B Thinking

Added Aug 26, 2025Open weights

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Use in the app

Qwen3 Vision‑Language model built on a 235B MoE backbone (≈22B active per token). Strong at OCR, charts/tables, multi‑image reasoning, and complex document understanding. The Thinking variant enables long‑form, chain‑of‑thought style reasoning.

  • Reasoning
  • Vision
Input
Text, Images
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.50
Output
$6.00

Reference prices as published by the model provider. API example

Specifications

Context window
—
Max output
32.8K

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Qwen3 VL 235B A22B Thinking compared

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

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Qwen3 VL 235B A22B ThinkingQwenThis modelGLM 4.6 OriginalZ.aiRemove
ProviderQwenZ.ai
Discovery tierOpen weightsOpen weights
AddedAug 26, 2025Dec 11, 2025
Limits
Context window—256K
Max output32.77K65.54KBest
Average output—1.3K tokens
Pricing, USD per 1M tokens
Input$0.50$0.50
Output$6.00$2.00Best
Cache read—$0.10
Performance
Request success (24h)—99.5%
Benchmark indexes
Intelligence Index—14.9
Math Index—44.3
Capabilities
ReasoningYesYes
ToolsNoYes
VisionYesNo
Reasoning effort——

Public evaluations

Benchmarks

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

  • Qwen3 VL 235B A22B Thinking
  • GLM 4.6 Original

Intelligence Index

  • Qwen3 VL 235B A22B Thinking—
  • GLM 4.6 Original14.9
3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 44.3

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 26.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 5.5%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 63.2%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 78.4%

  • IFBench

    Following precise output instructions

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 36.7%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 56.1%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 44.3%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 28.8%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 76.9%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3 VL 235B A22B Thinking: —
    • GLM 4.6 Original: 26.3%

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": "qwen/qwen3-vl-235b-a22b-thinking",
    "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="qwen/qwen3-vl-235b-a22b-thinking",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.