Comparison
LLMDebugger vs eval-view
Verdict
Pick LLMDebugger if lLMDebugger offers step-by-step verification of runtime execution for large language models; pick eval-view if regression testing for AI agents to detect behavioral changes and output quality regressions over time.
Markdown twin · LLMDebugger alternatives · eval-view alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | LLMDebugger | eval-view |
|---|---|---|
| Maintenance | Dormant (693d since push) As of 2w · github_public_v1 | Very active (6d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-11 As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- LLMDebugger
- A Large Language Model Debugger verifying runtime execution step by step
- eval-view
- Regression testing for AI agents
Stars
- LLMDebugger
- 587
- eval-view
- 126
Forks
- LLMDebugger
- 56
- eval-view
- 21
Open issues
- LLMDebugger
- 5
- eval-view
- 3
Language
- LLMDebugger
- Python
- eval-view
- Python
Adopt for
- LLMDebugger
- LLMDebugger offers step-by-step verification of runtime execution for large language models.
- eval-view
- Regression testing for AI agents to detect behavioral changes and output quality regressions over time.
Persona
- LLMDebugger
- -
- eval-view
- -
Runtime
- LLMDebugger
- -
- eval-view
- -
License
- LLMDebugger
- The LLMDebugger is distributed under the Apache-2.0 license.
- eval-view
- The software uses the Apache-2.0 license, offering permissive terms for use and distribution.
Last pushed
- LLMDebugger
- Sep 10, 2024
- eval-view
- Jul 26, 2026
Categories
- LLMDebugger
- Developer Tools, Evaluation & Observability
- eval-view
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- LLMDebugger
- Dormant (18%)
- eval-view
- Very active (96%)
Days since push
- LLMDebugger
- 693d
- eval-view
- 6d
Open issues (now)
- LLMDebugger
- 5
- eval-view
- 3
OSV dependency advisories
- LLMDebugger
- No published findings from this source as of 2026-07-11
- eval-view
- No lockfile (source not queried)
Full report
- LLMDebugger
- Trust report
- eval-view
- Trust report
Shared compatibility
- Python · LLMDebugger: Python runtime · eval-view: Python runtime
Choose LLMDebugger if…
- Pricing: Free for use, based on its open-source nature with an Apache-2.0 license..
- Tags unique to LLMDebugger: acl'24, llm debugging, python debugger for ai, runtime verification.
- Also covers Developer Tools.
- When detailed step-by-step inspection of the runtime behavior of large language models is required, LLMDebugger can provide precise insights into each execution phase.
When NOT to use LLMDebugger
- Avoid using if you are only interested in higher-level performance metrics rather than the intricate details of runtime behavior, as LLMDebugger emphasizes step-by-step execution.
- Not recommended for teams lacking experience with Python or specific to this tool's installation and usage workflow that involves setting up a Conda environment.
Choose eval-view if…
- Pricing: Free to use under the terms of the Apache License, Version 2.0..
- Requirements: Python environment is required for installation and usage.; Installation with pip: `pip install evalview`; Offline support means no live API keys necessary for the basic diff functionality..
- Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, regression-testing.
- Also covers AI Agents.
- eval-view ships Docker support for self-hosted deployment.
- When you need to track and assess the behavior consistency of your AI agent across versions without involving live API calls.
When NOT to use eval-view
- If you do not need to monitor specific behavioral characteristics such as tool call sequences and parameter consistency over time.
- When real-time output quality evaluation is critical, as eval-view's offline diffing does not provide immediate feedback on output changes without an LLM judge.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (FloridSleeves/LLMDebugger) · observed Aug 5, 2026
- GitHub forks (FloridSleeves/LLMDebugger) · observed Aug 5, 2026
- Last push (FloridSleeves/LLMDebugger) · observed Sep 10, 2024
- License file (Apache-2.0) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (hidai25/eval-view) · observed Aug 2, 2026
- GitHub forks (hidai25/eval-view) · observed Aug 2, 2026
- Last push (hidai25/eval-view) · observed Jul 26, 2026
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LLMDebugger 587 · eval-view 126 (synced Aug 5, 2026).
Common questions
- What is the difference between LLMDebugger and eval-view?
- LLMDebugger: A Large Language Model Debugger verifying runtime execution step by step. eval-view: Regression testing for AI agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose LLMDebugger over eval-view?
- Choose LLMDebugger over eval-view when Pricing: Free for use, based on its open-source nature with an Apache-2.0 license.; Tags unique to LLMDebugger: acl'24, llm debugging, python debugger for ai, runtime verification; Also covers Developer Tools; When detailed step-by-step inspection of the runtime behavior of large language models is required, LLMDebugger can provide precise insights into each execution phase.
- When should I choose eval-view over LLMDebugger?
- Choose eval-view over LLMDebugger when Pricing: Free to use under the terms of the Apache License, Version 2.0.; Requirements: Python environment is required for installation and usage.; Installation with pip:
pip install evalview; Offline support means no live API keys necessary for the basic diff functionality.; Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, regression-testing; Also covers AI Agents; eval-view ships Docker support for self-hosted deployment; When you need to track and assess the behavior consistency of your AI agent across versions without involving live API calls. - When should I avoid LLMDebugger?
- Avoid using if you are only interested in higher-level performance metrics rather than the intricate details of runtime behavior, as LLMDebugger emphasizes step-by-step execution. Not recommended for teams lacking experience with Python or specific to this tool's installation and usage workflow that involves setting up a Conda environment.
- When should I avoid eval-view?
- If you do not need to monitor specific behavioral characteristics such as tool call sequences and parameter consistency over time. When real-time output quality evaluation is critical, as eval-view's offline diffing does not provide immediate feedback on output changes without an LLM judge.
- Is LLMDebugger or eval-view more popular on GitHub?
- LLMDebugger has more GitHub stars (587 vs 126). Stars measure visibility, not whether either tool fits your constraints.
- Are LLMDebugger and eval-view open source?
- Yes - both are open-source projects on GitHub (LLMDebugger: Apache-2.0, eval-view: Apache-2.0).
- Where can I find alternatives to LLMDebugger or eval-view?
- GraphCanon lists graph-backed alternatives at LLMDebugger alternatives and eval-view alternatives (LLMDebugger markdown twin, eval-view 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, LLMDebugger or eval-view?
- LLMDebugger: Dormant. eval-view: 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 LLMDebugger and eval-view?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLMDebugger trust report; eval-view trust report.