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#13AOct 9, 2026Evidence B

Qwen3.8-Flash

Alibaba · Undisclosed (MoE, ~12B active)

An A-tier ticket for ¥1.2

The fast sibling shipped the same day as Qwen3.8-Max. Composite 87.5 puts it in tier A at one-fifteenth of Max’s price — the first time a Flash-class model reaches A on this board, which redraws the price-performance Pareto frontier. Its ecosystem score of 97 is among the highest here: open weights, Apache-2.0, 256K context, one API from edge to cloud.

TextImageVideoGUINative

Last updated Oct 18, 2026Editorial scoring

Bottom line

For high-frequency image analysis with large inputs and small outputs — product tagging, batch receipt structuring, content moderation — Qwen3.8-Flash costs a fraction of a flagship per 1,000 images with an acceptable accuracy gap. It is the wrong tool for long-video temporal reasoning, creative generation, or any case where one wrong image is expensive.

Eight-dimension breakdown

editorial mapping · 0–100
Perception89Document90Chart QA86Video82Agent87Generation80Chinese88Ecosystem978D
  • Qwen3.8-Flash87.5
Visual perception & grounding20%
89
Document parsing & Chinese OCR18%
90
Chart & document reasoning14%
86
Video & long-horizon reasoning14%
82
GUI agents & tool use14%
87
Generation & editing6%
80
Chinese context & culture6%
88
Ecosystem, cost & availability8%
97

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 2026-1084.2#1 in its price class (official)
输出单价¥1.2≈ 1/15 of Max
上下文256KHighest in class

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 OCR90 · Near-flagship on clean receipts
Chart data extraction85 · Fine single-figure; drops on cross-page
30-min video QA80 · Noticeable event-localization drift
Mobile GUI control86 · Steady single steps; long tasks need rollback
Chinese cultural context88 · Common memes fine, obscure allusions not

Strengths and limitations

Strengths

  • ¥1.2/1M output tokens plus a tier-A composite leaves almost nothing to beat on value.
  • Apache-2.0 open weights, self-hostable, and shares an API with Max — enabling a Flash-triage plus Max-review relay.
  • 256K context is unmatched at this price, so long-document triage needs less chunking.

Limitations

  • Video timing is only 82; event localization drifts on long clips, so it should not carry video QA.
  • Generation and editing at 80, with Chinese glyph error rates a tier above the flagship.
  • It gets hard cases confidently wrong and lacks Max’s self-checking, so sampled review is mandatory.

Price and real cost

List price

¥1.2/M tokens

≈ ¥1.2 / 1M output tokens. For 1,000 images at 1,024px, ~1,100 image tokens each and 300 output tokens, the monthly cost is about ¥0.7 (assuming input at 25% of output price).

Use your volume

About Qwen3.8-Flash

Is Qwen3.8-Flash open source?

Licence: Open weights (Apache-2.0). Weights are available, but check the exact terms and filing requirements before commercial use.

How much does Qwen3.8-Flash cost?

≈ ¥1.2 / 1M output tokens. It ranks #13 with a composite of 87.5. Real bills depend on resolution, tiling, caching and volume discounts.

What is Qwen3.8-Flash best for?

High-volume product tagging and moderation; Batch receipt structuring with flagship sampling; Edge or low-cost on-prem deployment。

Why does Qwen3.8-Flash score 87.5?

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.