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Qwen · Balanced

Qwen3.5 Plus

Added Feb 16, 2026

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Use in the app

Qwen 3.5 Plus is a commercial model with hybrid linear attention and sparse MoE architecture. Supports text, image, and video input with a 1M context window.

  • Vision
  • Video input
Input
Text, Images, Video
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.40
Output
$2.40
Cache read
$0.04

Reference prices as published by the model provider. API example

Specifications

Context window
983.6K
Max output
65.5K
Average output (7 days)
141 tokens
Longer than 14% of 468 models

Side by side

Qwen3.5 Plus compared

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

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Qwen3.5 PlusQwenThis modelMistral Medium 3MistralRemove
ProviderQwenMistral
Discovery tierBalancedBalanced
AddedFeb 16, 2026Sep 25, 2025
Limits
Context window983.62KBest131.07K
Max output65.54KBest32.77K
Average output141 tokens683 tokens
Pricing, USD per 1M tokens
Input$0.40$0.40
Output$2.40$2.00Best
Cache read$0.04—
Performance
Throughput—107.8 tok/s
Time to first token—0.7 s
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index—9.0
Math Index—30.3
Capabilities
VisionYesYes
Video inputYesNo
Reasoning effort——

Public evaluations

Benchmarks

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

  • Qwen3.5 Plus
  • Mistral Medium 3

Intelligence Index

  • Qwen3.5 Plus—
  • Mistral Medium 39.0
3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 30.3

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 31.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 4.1%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 57.8%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 76.0%

  • IFBench

    Following precise output instructions

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 39.3%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 40.0%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 30.3%

  • AIME

    Competition mathematics

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 44.0%

  • MATH-500

    Competition math problems

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 90.7%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 3.8%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 24.3%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.5 Plus: —
    • Mistral Medium 3: 31.3%

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/qwen3.5-plus",
    "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/qwen3.5-plus",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.