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Qwen3.8 Flash

Added Aug 26, 2026Open weights

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Use in the app

Qwen3.8 Flash is Alibaba's latest fast multimodal model, with a million-token context window for coding, agentic workflows, visual understanding, long documents, codebases, and videos.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Video input
Input
Text, Images, Video
Output
Text
Reasoning effort
none · high
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.14
Output
$0.42
Cache read
$0.016
Cache write
$0.20

Reference prices as published by the model provider. API example

Specifications

Context window
991.8K
Max output
131.1K

Side by side

Qwen3.8 Flash compared

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

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Qwen3.8 FlashQwenThis modelMiMo V2.6 FlashxiaomiRemove
ProviderQwenxiaomi
Discovery tierOpen weightsOpen weights
AddedAug 26, 2026Sep 21, 2026
Limits
Context window991.81K1.05MBest
Max output131.07K131.07K
Average output—818 tokens
Pricing, USD per 1M tokens
Input$0.14$0.14
Output$0.42$0.28Best
Cache read$0.016$0.0028Best
Cache write$0.20$0.00Best
Performance
Throughput—34.3 tok/s
Time to first token—2.2 s
Request success (24h)96.5%99.3%Best
Benchmark indexes
Intelligence Index—37.9
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
Audio inputNoYes
Video inputYesYes
Reasoning effortnone, highnone, high

Public evaluations

Benchmarks

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

  • Qwen3.8 Flash
  • MiMo V2.6 Flash

Intelligence Index

  • Qwen3.8 Flash—
  • MiMo V2.6 Flash37.9
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 64.1%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 31.5%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 1,488 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 1,609 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 9.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 74.3%

  • MLCR-AA

    Long-context reasoning over medical records

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 11.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 35.1%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 22.7%

  • SciCode

    Scientific computing in Python

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 51.3%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.8 Flash: —
    • MiMo V2.6 Flash: 74.3%

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.

Prompt cache hits
96.2%
About $0.0207 per 1M input tokens with caching
Request success (24h)
96.5%
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 77.9%
  • 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": "qwen/qwen3.8-flash",
    "reasoning_effort": "none",
    "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/qwen3.8-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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