Mirendil says Fern 0.1 was trained for under $10M with agents writing more than 99 percent of the…
The open-weight release brings a 128K context window and doubled vocabulary to agents that run without a cloud…
d1 returns calibrated probabilities for fixed choices and spends zero output tokens on the answer.
Speculative-decoding checkpoints from Liquid AI boost LFM2.5 throughput by up to 3.18x without changing outputs.
The open-weights edge model adds tool calling and strong screen grounding to the LFM family.
Liquid AI's 2.6B model plans, calls tools, and runs fully on-device with a 128K context.