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Model for local agents and specialized applications, 1.73B parameters, tri-hybrid architecture (13 gated short convolutions, 5 sliding-window attention, 6 global attention). Explicit agentic post-training (harnesses like Hermes Agent, Pi, OpenClaw), 256K-token context, 16 languages including Italian, ~1GB of RAM at 4-bit. LFM Open License v1.0.
80GB HBM2e datacenter GPU: the standard for datacenter training and inference. Requires dedicated servers and enterprise power.
The top-tier datacenter GPU with 80GB HBM3: the top-of-the-line for large-model training and inference. Enterprise configurations only.
The world's most powerful consumer GPU for local training and high-speed inference.
