NOUMENOpen app
NOUMEN

Qwen · Efficient

Qwen3.8 Omni Flash

Added Sep 17, 2026

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Use in the app

Qwen3.8 Omni Flash is a fast omni-modal reasoning model for understanding text, images, audio, and video. It is especially suited to meeting summaries, transcripts and subtitles, speaker-aware audiovisual analysis, and long-form content review. It returns text and supports a nearly one-million-token context window, tool calling, and structured output.

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

Pricing

USD per 1M tokens
Input
$0.15
Output
$0.47
Cache read
$0.016

Reference prices as published by the model provider. API example

Specifications

Context window
991.8K
Max output
131.1K

Side by side

Qwen3.8 Omni Flash compared

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

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Qwen3.8 Omni FlashQwenThis modelMiniMax M3.1 FlashMiniMaxRemove
ProviderQwenMiniMax
Discovery tierEfficientEfficient
AddedSep 17, 2026Oct 19, 2026
Limits
Context window991.81K1.05MBest
Max output131.07K524.29KBest
Average output—1.4K tokens
Pricing, USD per 1M tokens
Input$0.15$0.15
Output$0.47Best$0.60
Cache read$0.016$0.015Best
Performance
Throughput—119.8 tok/s
Time to first token—7.0 s
Request success (24h)100.0%Best99.7%
Benchmark indexes
Intelligence Index—42.7
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesNo
Audio inputYesNo
Video inputYesYes
Reasoning effortnone, highlow, medium, high, xhigh, max

Public evaluations

Benchmarks

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

  • Qwen3.8 Omni Flash
  • MiniMax M3.1 Flash

Intelligence Index

  • Qwen3.8 Omni Flash—
  • MiniMax M3.1 Flash42.7
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 72.5%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 38.1%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 1,473 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 1,458 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 20.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 79.7%

  • MLCR-AA

    Long-context reasoning over medical records

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 16.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 48.0%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 25.8%

  • SciCode

    Scientific computing in Python

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 53.4%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.8 Omni Flash: —
    • MiniMax M3.1 Flash: 79.7%

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
0.0%
About $0.15 per 1M input tokens with caching
Request success (24h)
100.0%
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 100.0%
  • 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-omni-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-omni-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.