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Google: Gemma 3 27B

Google

balanced

Capabilities

VisionToolsStructured OutputLong ContextCode

Strengths

  • Open weights enable full local privacy control
  • Strong multimodal (vision+text) capability at accessible price
  • Excellent long-context handling (262K tokens)
  • Multilingual support (140+ languages)
  • Competitive conversation and generation quality

Weaknesses

  • Vision performance lags behind flagship models
  • Non-commercial license restricts enterprise deployment
  • Smaller than flagship models; lower reasoning ceiling
  • Training data composition not fully transparent

Pricing

Input / 1M tokens

$0.08

Output / 1M tokens

$0.44999999999999996

Context window

262.144k

Transparency

Open weights

10.0 / 10

Open training data

0.0 / 10

Open methodology

6.5 / 10

Licence openness

7.0 / 10

Provider disclosure

6.0 / 10

FMTI company score

N/A

Composite:4.5 / 10

Gemma 3 27B ships with open weights under a non-commercial license. Google publishes model cards and some training details, but full training data and methodology remain proprietary. Open-weight status enables self-hosting and local deployment for privacy-conscious users.

Sustainability

Inference energy

N/A

Training footprint

N/A

Provider infrastructure

7.5 / 10

Composite:6.2 / 10

Google operates among the world's largest renewable energy commitments, powering data centers with substantial clean energy. 27B parameter size is moderate, suggesting lower per-inference energy than flagship models. Training footprint unknown but Google's infrastructure advantage is material.

Task Fitness

question answering
76%
code
72%
mathematics
67%
business communication
72%
vision
59%
analysis
66%
extraction
65%
long-form generation
76%
research
65%
reasoning
74%
summarisation
72%
translation
70%
conversation
77%