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#03S+Mar 8, 2026Evidence A

Qwen3.5-397B-A17B

Alibaba · 397B total / 17B active (MoE)

The multimodal flagship that behaves like infrastructure

SuperCLUE-VLM 88.50, strongest in document parsing and multilingual OCR. 32-language OCR, 256K context and a full open-weight matrix make it the easiest enterprise bet.

TextImageVideoAudioNative

Last updated Oct 18, 2026Editorial scoring

Bottom line

Qwen3.5 is the “you will not regret it” pick: documents, charts, multilingual and on-prem all work, with the most complete tooling. It concedes the hardest reasoning to text specialists, and the flagship is not open.

Eight-dimension breakdown

editorial mapping · 0–100
Perception96Document97Chart QA95Video92Agent92Generation90Chinese94Ecosystem988D
  • Qwen3.5-397B-A17B94.6
Visual perception & grounding20%
96
Document parsing & Chinese OCR18%
97
Chart & document reasoning14%
95
Video & long-horizon reasoning14%
92
GUI agents & tool use14%
92
Generation & editing6%
90
Chinese context & culture6%
94
Ecosystem, cost & availability8%
98

Weights: perception 20 / documents 18 / charts 14 / video 14 / agents 14 / generation 6 / Chinese 6 / ecosystem 8. Definitions and sources on the methodology page.

Public benchmarks

as reported, not converted
Benchmark / metricValueNote
SuperCLUE-VLM 2026-0488.50Qwen3.5-397B-A17B-Thinking
OCR 语言覆盖32Qwen3-VL family, official
上下文256KExpandable to 1M

Public scores come from different versions and prompts and are not interchangeable with our composite; they are one evidence input.

Scenario mapping

five stress tests, one scale
ScenarioScoreObservation
Chinese receipt OCR96 · Good layout fidelity and field alignment
Chart data extraction95 · Strong cross-page comparison
30-min video QA91 · Slightly behind Doubao on long video
Mobile GUI control91 · Stable UI element grounding
Chinese cultural context94 · Solid local knowledge

Strengths and limitations

Strengths

  • Best-balanced document and 32-language OCR; table structure is stable.
  • A full 8B-to-397B matrix, one API from edge to cloud.
  • Richest open ecosystem and fine-tuning tooling; cheapest community reproduction.

Limitations

  • The flagship is closed; only small and mid sizes are truly self-hostable.
  • Details late in very long documents can slip; chunking plus retrieval is advised.
  • Large capability gaps between sizes make mis-selection easy.

Price and real cost

List price

¥12/M tokens

≈ ¥12 / 1M output tokens. For 1,000 images at 1,024px, ~1,100 image tokens each and 300 output tokens, the monthly cost is about ¥7.3 (assuming input at 25% of output price).

Use your volume

About Qwen3.5-397B-A17B

Is Qwen3.5-397B-A17B open source?

Licence: Smaller sizes open (Apache-2.0); flagship closed. No public weights; access is via vendor API or an on-prem licence.

How much does Qwen3.5-397B-A17B cost?

≈ ¥12 / 1M output tokens. It ranks #3 with a composite of 94.6. Real bills depend on resolution, tiling, caching and volume discounts.

What is Qwen3.5-397B-A17B best for?

Enterprise document hubs and contract review; Multilingual product data extraction; On-prem public-sector projects。

Why does Qwen3.5-397B-A17B score 94.6?

The composite weights eight dimensions: perception 20%, documents 18%, charts 14%, video 14%, agents 14%, generation 6%, Chinese 6%, ecosystem 8%. Its strongest dimension is Ecosystem, cost & availability; its weakest is Generation & editing.

Personal ranking · Not an official score

Every ranking, score and comparison on this page is an independent personal ranking, not an official score, and represents no vendor, institution or regulator. Scores are a subjective mapping of public evidence under our own weights — change the weights and the order changes. Disagree, or spotted a factual error? Contact the site owner: jizhi2024@foxmail.com — we check each report and log corrections in the changelog.