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ainekko/smolvla_base_onnx; large weight tensors
are stored as fp16 and cast back to fp32 at use, so compute stays fp32-accurate (action output
matches the fp32 reference to ~2.5e-4) while the download shrinks 1.58 GB → 831 MB.smolvlm_vision (image [1,3,512,512] → [1,64,960]) · smolvlm_text (token embeddings) ·
smolvlm_expert_prefill / smolvlm_expert_decode (VLM + action expert, 16 KV layers) ·
state_projector · action_in/out_projector · time_in/out_projector.embed_prefix (vision·√d ‖ text·√d ‖ state, padded to 177) → prefill (16-layer KV
cache) → 10-step Euler denoise (action_in ⊕ sinusoidal-time → time MLP → decode with KV →
action_out = velocity) → action chunk [50, 32]. Reference orchestrator:
robobrowser/smolvla.js.