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Qwen: Qwen3.5-9B

Alibaba

open_source_balanced

Capabilities

VisionToolsStructured OutputExtended ThinkingLong ContextCode

Strengths

  • Excellent vision and multimodal understanding for 9B class
  • 262K context window enables long document processing
  • Open weights allow full self-hosting and fine-tuning
  • Strong reasoning and structured output capability

Weaknesses

  • Extremely slow inference (0.02 speed score)
  • Coding performance moderate for size (0.53)
  • Analysis and QA fitness below balanced tier average
  • Training data transparency limited

Pricing

Input / 1M tokens

$0.09999999999999999

Output / 1M tokens

$0.15

Context window

262.144k

Transparency

Open weights

10.0 / 10

Open training data

0.0 / 10

Open methodology

7.5 / 10

Licence openness

8.5 / 10

Provider disclosure

7.0 / 10

FMTI company score

N/A

Composite:6.5 / 10

Open-weight model with published architecture and training details. Alibaba publishes model cards and capability reports. Training data sources not fully disclosed. Apache 2.0 license enables commercial and research use.

Sustainability

Inference energy

7.8 / 10

Training footprint

N/A

Provider infrastructure

6.0 / 10

Composite:7.0 / 10

9B parameter size implies low inference energy relative to flagship models; supports efficient deployment on consumer hardware. Alibaba's sustainability commitments partially disclosed; no explicit green infrastructure data published for this model.

Task Fitness

question answering
37%
code
53%
mathematics
50%
business communication
50%
vision
72%
analysis
46%
extraction
56%
long-form generation
68%
research
50%
reasoning
52%
summarisation
72%
translation
65%
conversation
70%