Tom Aarsen: Credit to the Perplexity Research team for the models. Both are MIT licensed. pip install "sentence-transformers>=6.0.0" "transformers>=5.4.0" huggingface.co/collections/...
Tom Aarsen: The 0.6B model starts from Qwen3.5-0.8B, with its text tower pruned from 24 to 12 layers. 594M total parameters, but only ~240M active for text encoding & ~340M for images. The large embedding tabl…
Tom Aarsen: Retrieval gains also carry into agent answers. On BrowseComp+, Perplexity's GPT-OSS-120B agent with the 9B retriever reaches 64.0% accuracy: +4.9 points over the next best evaluated ColBERT model, …