GreenPT green-embedding (Qwen3-Embedding-4B)
GreenPT
Capabilities
Strengths
- 100% renewable energy inference
- Heat recovery — server heat heats buildings
- EU-hosted GDPR compliant
- 100+ languages
- Matryoshka — 32 to 2560 dim
- Qwen3-Embedding-4B backbone (open model under green infrastructure)
Weaknesses
- Subscription required for API
- Single provider — smaller community than Cohere / OpenAI
Pricing
Input / 1M tokens
$0.22
Output
—
Hosting
Hosted only
Embedding specs
Output dimension
2560
Max input
32,000 tokens
Matryoshka
Supported
Matryoshka representation learning: dimension can be truncated to a smaller size at index time without retraining, trading retrieval quality for index size and speed.
Transparency
Open weights
10.0 / 10
Open training data
4.0 / 10
Open methodology
6.0 / 10
Licence openness
8.0 / 10
Provider disclosure
8.5 / 10
FMTI company score
N/A
Open-source backbone; hosting infrastructure documented.
Sustainability
Inference energy
9.8 / 10
Training footprint
N/A
Provider infrastructure
9.5 / 10
100% renewable energy + heat recovery. Best-in-class for hosted embedding.
MTEB quality
Grounded in the MTEB (Massive Text Embedding Benchmark) Overall average published by the model authors. Bearing collapses MTEB's retrieval, STS, classification, and clustering categories into a single quality signal because they correlate strongly for embedding models. Methodology.