Maverick: Private and Verifiable LLM Inference Made Practical via Matrix-Vector Multiplication Delegation
Maverick protocol delivers private and verifiable LLM inference via matrix-vector multiplication delegation, achieving up to 45x throughput gains over local inference on Qwen3-4B.
Maverick introduces an information-theoretically sound protocol for delegating matrix-vector multiplication with transparent preprocessing, efficient batch verification, and virtually no server overhead, combined with LPN-based pseudorandom masking for input privacy. It addresses privacy and correctness concerns when users delegate open-weight LLM inference to third-party providers. An end-to-end prototype evaluated on Qwen3-4B achieved throughput gains over local inference of up to 45x with precomputed privacy masks and 44x for verification-only workloads, with a CPU server using up to 128 threads.