Alibaba

Qwen3.8 27B (low)Open

Alibaba Qwen3.8 27B (low) model with 260K context window, optimized for advanced reasoning and multimodal tasks.

#279released Aug 14, 2026·Open Weights·27 billion
textimagevideo260K ctxeffort: low
API providersGet API Key →Leaderboard
Intelligence
65.0 #279
AAQI 30.0
Output Speed
64 t/s
TTFT 3.03 s · ITL 15.6 ms/tok
Blended price (3:1)
$1.125 /1M
In $0.5/M · Out $3/M
Context
260K
≈ 650 A4 pages · max out 8,192

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

Qwen3.8 27B (low)
Claude Mythos Preview (#1)
Average (68)
Coding (63)Mathematics (39)Hard Science (GPQA) (45)Agentic & Tool Use (36)Knowledge (MMLU) (39)Vision / Multimodal (36)

Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.

Strengths & Trade-offs

Where it wins

  • Open weights — self-host, fine-tune and audit with no vendor lock-in
  • Cheap prompt-cache reads at $0.05/1M
  • Native multimodality across text, image, video

Killer Use Cases

Math & proof work
Step-verified reasoning for olympiad math, theorem proving and formal verification.
Vision & document OCR
Extracts structure from scans, charts, screenshots and mixed-media inputs.
On-prem deployment
Air-gapped and regulated-environment serving on your own hardware.

Developer Quickstart & API

Set DASHSCOPE_API_KEY first — get an API key
curl https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "qwen3-8-27b-low",
    "messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
  }'

Official Resources & Links

API deployment

Compare hosts & latency

Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
View providers matrix →

Scores by Source

Live Specs & Architecture

Under the hood
Dense · 27 billion
  • Prompt caching supported — cached input reads at $0.05/1M tokens.
  • Native multimodality: text, image, video in a single model.
Release date
Aug 14, 2026
Architecture
Dense · 27 billion
Parameters
27 billion
License
Open Weights
Context Window
260,000 tokens
Max Output
8,192 tokens
Modalities
text + image + video
Cache Pricing
read $0.05 · write $0.625 /1M
Reasoning
—
Input Price
$0.5/M
Output Price
$3/M
Output Speed
64 t/s
Time to First Token
3.03 s
Data Updated
Aug 14, 2026

Estimated monthly bill

Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...

Cite & embed

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BibTeX
@misc{llmpodium2026qwen3827blow,
  title = {Benchmark Analysis and Intelligence Evaluation of Qwen3.8 27B (low)},
  author = {LLMPodium Research},
  year = {2026},
  url = {https://llmpodium.com/models/qwen3-8-27b-low}
}

Embed Score Badge

Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.

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Qwen3.8 27B (low) LLMPodium Score
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