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Qwen · Open weights

Qwen3.8 27B TEE

Added Aug 24, 2026Open weights

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Use in the app

Qwen3.8 27B is an open-weight dense vision-language model from Alibaba for reasoning, coding, professional workflows, multimodal interaction, tool use, and structured output. Running inside a TEE (Trusted Execution Environment), with provider attestation support.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Video input
Input
Text, Images, Video
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.40
Output
$3.00
Cache read
$0.15

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
262.1K
Average output (7 days)
301 tokens
Longer than 32% of 468 models

Side by side

Qwen3.8 27B TEE compared

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

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Qwen3.8 27B TEEQwenThis modelQwen 3.8 27B DarkIdolQwenRemove
ProviderQwenQwen
Discovery tierOpen weightsOpen weights
AddedAug 24, 2026Oct 5, 2026
Limits
Context window262.14K262.14K
Max output262.14KBest32.77K
Average output301 tokens554 tokens
Pricing, USD per 1M tokens
Input$0.40$0.10Best
Output$3.00$0.60Best
Cache read$0.15$0.05Best
Performance
Throughput—40.9 tok/s
Time to first token—2.2 s
Request success (24h)100.0%Best90.3%
Benchmark indexes
Intelligence Index20.2—
Coding Index44.6—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesNo
Video inputYesNo
Reasoning effort——

Public evaluations

Benchmarks

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

  • Qwen3.8 27B TEE
  • Qwen 3.8 27B DarkIdol

Intelligence Index

  • Qwen3.8 27B TEE20.2
  • Qwen 3.8 27B DarkIdol—

Qwen3.8 27B TEE: Better than 50% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Qwen3.8 27B TEE: 44.6
    • Qwen 3.8 27B DarkIdol: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen3.8 27B TEE: 12.4%
    • Qwen 3.8 27B DarkIdol: —

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen3.8 27B TEE: 1.5%
    • Qwen 3.8 27B DarkIdol: —

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen3.8 27B TEE: 898 Elo
    • Qwen 3.8 27B DarkIdol: —

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen3.8 27B TEE: 1,074 Elo
    • Qwen 3.8 27B DarkIdol: —

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen3.8 27B TEE: 5.2%
    • Qwen 3.8 27B DarkIdol: —

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.8 27B TEE: 69.3%
    • Qwen 3.8 27B DarkIdol: —

  • MLCR-AA

    Long-context reasoning over medical records

    • Qwen3.8 27B TEE: 10.0%
    • Qwen 3.8 27B DarkIdol: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.8 27B TEE: 12.1%
    • Qwen 3.8 27B DarkIdol: —

  • GPQA Diamond

    Graduate-level science questions

    • Qwen3.8 27B TEE: 81.8%
    • Qwen 3.8 27B DarkIdol: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen3.8 27B TEE: 0.0%
    • Qwen 3.8 27B DarkIdol: —

  • SciCode

    Scientific computing in Python

    • Qwen3.8 27B TEE: 36.2%
    • Qwen 3.8 27B DarkIdol: —

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.8 27B TEE: 69.3%
    • Qwen 3.8 27B DarkIdol: —

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
34.1%
About $0.31 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": "TEE/qwen3.8-27b",
    "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="TEE/qwen3.8-27b",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.