Mirendil says Fern 0.1 was trained for under $10M with agents writing more than 99 percent of the…
A 340M-parameter classifier from Fastino returns typed answers with confidence scores for agent pipelines.
The Caltech spinout squeezed an Alibaba model to 5.9GB while keeping 98 percent of its benchmark scores.
Cactus Compute's new model packs tool calling into 45M parameters and a 14MB binary.