# inference-labs-inc/dsperse

Distributed zkML

Repository: https://github.com/inference-labs-inc/dsperse
Canonical: https://ross.abutalabs.com/products/dsperse
Homepage: https://pypi.org/project/dsperse/
Language: Rust
License: NOASSERTION
License Family: other
Topics: zkml
Last push: 2026-07-14T15:01:25+00:00

## Health v2 (maintenance only)
Score: 82/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 92, release rhythm 93, longevity 39
- inputs: {"age_days": 548, "days_push": 50, "days_rel": 51, "gap_med": 0.0, "n_releases_24m": 25}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1327, forks 14 (observed 2026-08-28T04:04:22.952248+00:00)

## What it is
DSperse is a proving-system-agnostic tool for verifiable AI that decomposes ONNX neural network models into circuit-compatible segments and orchestrates compilation, inference, proving, and verification across pluggable zero-knowledge proof backends. It is written in Rust with Python bindings and a CLI, supporting backends like JSTprove and Expander.

## Use cases
- generate zero-knowledge proofs of neural network inference
- split an ONNX model into circuit-compatible slices
- verify that an ML model was executed correctly without revealing weights
- run inference on a sliced model with chained segment outputs
- tile large convolutions for zk-circuit execution
- prove ML model execution across pluggable ZK backends

## When to choose
- you need verifiable or zero-knowledge machine learning inference on ONNX models
- you want a full slice-compile-run-prove-verify pipeline via CLI or Rust/Python APIs
- you need a proof-system-agnostic zkML framework with pluggable backends

## When to avoid
- you just need standard fast inference without cryptographic proofs
- your models are not in ONNX format
- you need a mature production system - the project is relatively early-stage with a non-standard license

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, llm-inference, cryptography, cli, compiler
- domain: machine-learning, artificial-intelligence, developer-tools
- platform: rust, python, cli, cross-platform
- tags: zkml, zero-knowledge-proofs, onnx, model-slicing, verifiable-ai, proof-systems, cryptography, linux, macos

## Member repositories
- inference-labs-inc/dsperse (main) score 82

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:22.952248+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:46:17.479502+00:00, confidence not recorded.
  - readme: https://github.com/inference-labs-inc/dsperse (fetched 2026-08-28T04:04:22.952248+00:00, sha dc1e700569f2)
  - homepage: https://pypi.org/project/dsperse/ (fetched 2026-08-29T12:05:05.948075+00:00, sha 4b4e8fead74a)
- Data as of 2026-08-30T08:39:29.467469+00:00.