Comparison
netron vs onnx-mlir
Verdict
Pick netron if netron is an open-source visualizer for neural networks with support across multiple frameworks including TensorFlow, PyTorch, and ONNX; pick onnx-mlir if oNNX-MLIR is optimised for compiling ONNX models to MLIR and LLVM bytecodes, offering cross-platform support and multiple runtime environments.
Markdown twin · netron alternatives · onnx-mlir alternatives
GraphCanon updated Sep 30, 2026
12views this month
Trust & integrity
| Signal | netron | onnx-mlir |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 27, 2026 · github_public_v1 | Very active (0d since push) As of Sep 30, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 27, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 30, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- netron
- Visualizer for neural network, deep learning and machine learning models
- onnx-mlir
- ONNX model compiler technology lowering ONNX graphs to MLIR and LLVM bytecodes
Stars
- netron
- 34k
- onnx-mlir
- 1.1k
Forks
- netron
- 3.2k
- onnx-mlir
- 451
Open issues
- netron
- 18
- onnx-mlir
- 367
Language
- netron
- JavaScript
- onnx-mlir
- MLIR
Adopt for
- netron
- Netron is an open-source visualizer for neural networks with support across multiple frameworks including TensorFlow, PyTorch, and ONNX.
- onnx-mlir
- ONNX-MLIR is optimised for compiling ONNX models to MLIR and LLVM bytecodes, offering cross-platform support and multiple runtime environments.
Persona
- netron
- -
- onnx-mlir
- -
Runtime
- netron
- -
- onnx-mlir
- -
License
- netron
- MIT
- onnx-mlir
- Available under the Apache License Version 2.0 (Apache-2.0). Permissions granted for reproduction, distribution, etc., as per license terms.
Last pushed
- netron
- Sep 26, 2026
- onnx-mlir
- Sep 29, 2026
Categories
- netron
- Inference & Serving, Model Training
- onnx-mlir
- Inference & Serving, Model Training
Trust and health
Open issues (now)
- netron
- 18
- onnx-mlir
- 367
Stars delta
- netron
- +222 (30d)
- onnx-mlir
- +19 (30d)
Open issues delta
- netron
- 0 (30d)
- onnx-mlir
- +15 (30d)
Owner type
- netron
- User
- onnx-mlir
- Organization
Full report
- netron
- Trust report
- onnx-mlir
- Trust report
Shared compatibility
- Python · netron: Python runtime · onnx-mlir: Python runtime
Choose netron if…
- netron is primarily JavaScript; onnx-mlir is MLIR.
- License: netron is MIT, onnx-mlir is Apache-2.0.
- Tags unique to netron: ai, coreml, deep-learning, deeplearning.
- When you need to visualize models from various deep learning frameworks like TensorFlow, PyTorch, or ONNX in a single tool
When NOT to use netron
- In environments where access to the web is restricted and no offline capability of Netron can be utilized
- When specific advanced visualization features are required that may not be supported by Netron yet implemented in a competitor's tool
Choose onnx-mlir if…
- onnx-mlir is primarily MLIR; netron is JavaScript.
- License: onnx-mlir is Apache-2.0, netron is MIT.
- Tags unique to onnx-mlir: compiler, llvm, mlir, onnx.
- For users needing compile-time optimization of ONNX models to improve inference performance in a variety of language runtimes such as C++, Java, and Python
When NOT to use onnx-mlir
- When quick setup and environment management are desired without using prebuilt containers, as setting up prerequisites manually may be challenging
- For teams primarily focused on real-time inference serving with dedicated AI hardware that requires specialized frameworks not covered by ONNX-MLIR's support matrix
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (lutzroeder/netron) · observed Sep 27, 2026
- GitHub forks (lutzroeder/netron) · observed Sep 27, 2026
- Last push (lutzroeder/netron) · observed Sep 26, 2026
- License file (MIT) · observed Sep 27, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (onnx/onnx-mlir) · observed Sep 30, 2026
- GitHub forks (onnx/onnx-mlir) · observed Sep 30, 2026
- Last push (onnx/onnx-mlir) · observed Sep 29, 2026
- License file (Apache-2.0) · observed Sep 30, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: netron 34k · onnx-mlir 1.1k (synced Sep 27, 2026).
Common questions
- What is the difference between netron and onnx-mlir?
- netron: Visualizer for neural network, deep learning and machine learning models. onnx-mlir: ONNX model compiler technology lowering ONNX graphs to MLIR and LLVM bytecodes. See the comparison table for live GitHub stats and shared categories.
- When should I choose netron over onnx-mlir?
- Choose netron over onnx-mlir when netron is primarily JavaScript; onnx-mlir is MLIR; License: netron is MIT, onnx-mlir is Apache-2.0; Tags unique to netron: ai, coreml, deep-learning, deeplearning; When you need to visualize models from various deep learning frameworks like TensorFlow, PyTorch, or ONNX in a single tool.
- When should I choose onnx-mlir over netron?
- Choose onnx-mlir over netron when onnx-mlir is primarily MLIR; netron is JavaScript; License: onnx-mlir is Apache-2.0, netron is MIT; Tags unique to onnx-mlir: compiler, llvm, mlir, onnx; For users needing compile-time optimization of ONNX models to improve inference performance in a variety of language runtimes such as C++, Java, and Python.
- When should I avoid netron?
- In environments where access to the web is restricted and no offline capability of Netron can be utilized When specific advanced visualization features are required that may not be supported by Netron yet implemented in a competitor's tool
- When should I avoid onnx-mlir?
- When quick setup and environment management are desired without using prebuilt containers, as setting up prerequisites manually may be challenging For teams primarily focused on real-time inference serving with dedicated AI hardware that requires specialized frameworks not covered by ONNX-MLIR's support matrix
- Is netron or onnx-mlir more popular on GitHub?
- netron has more GitHub stars (33,524 vs 1,058). Stars measure visibility, not whether either tool fits your constraints.
- Are netron and onnx-mlir open source?
- Yes - both are open-source projects on GitHub (netron: MIT, onnx-mlir: Apache-2.0).
- Where can I find alternatives to netron or onnx-mlir?
- GraphCanon lists graph-backed alternatives at netron alternatives and onnx-mlir alternatives (netron markdown twin, onnx-mlir markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, netron or onnx-mlir?
- netron: Very active. onnx-mlir: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for netron and onnx-mlir?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: netron trust report; onnx-mlir trust report.