--- title: "eval-view vs WeaveBench" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hidai25-eval-view-vs-weavebench-weavebench" tools: ["hidai25-eval-view", "weavebench-weavebench"] --- # eval-view vs WeaveBench *GraphCanon updated Sep 20, 2026* ## Verdict Pick eval-view if eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and; pick WeaveBench if weaveBench is designed for evaluating computer-use agents that integrate both GUI and CLI interactions in real-world scenarios across various work domains. [eval-view](https://evalview.com) reports 134 GitHub stars, 24 forks, and 2 open issues, last pushed Sep 5, 2026. [WeaveBench](https://weavebench.github.io) has 167 stars, 4 forks, and 5 open issues, last pushed Aug 22, 2026. Figures are from public GitHub metadata via [eval-view's repository](https://github.com/hidai25/eval-view) and [WeaveBench's repository](https://github.com/weavebench/WeaveBench). | | [eval-view](/tools/hidai25-eval-view.md) | [WeaveBench](/tools/weavebench-weavebench.md) | | --- | --- | --- | | Tagline | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | A Long-Horizon Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces | | Stars | 134 | 167 | | Forks | 24 | 4 | | Open issues | 2 | 5 | | Language | Python | Python | | Adopt for | Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and | WeaveBench is designed for evaluating computer-use agents that integrate both GUI and CLI interactions in real-world scenarios across various work domains. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [eval-view](/tools/hidai25-eval-view.md) | [WeaveBench](/tools/weavebench-weavebench.md) | | --- | --- | --- | | Days since push | 13d | 28d | | Open issues (now) | 2 | 5 | | Stars delta | +8 (30d) | +10 (30d) | | Open issues delta | -1 (30d) | +1 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/hidai25-eval-view/trust.md) | [trust report](/tools/weavebench-weavebench/trust.md) | ## Decision facts: eval-view - **Adopt for:** Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and ## Decision facts: WeaveBench - **Adopt for:** WeaveBench is designed for evaluating computer-use agents that integrate both GUI and CLI interactions in real-world scenarios across various work domains. ## Choose when ### Choose eval-view if… - License: eval-view is Apache-2.0, WeaveBench is MIT. - Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents. - eval-view ships Docker support for self-hosted deployment. - When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ### Choose WeaveBench if… - License: WeaveBench is MIT, eval-view is Apache-2.0. - Tags unique to WeaveBench: agent-as-judge, benchmark, computer-use-agent, gui-agent. - Use WeaveBench if you need to assess agents capable of handling tasks that require intermingling graphical user interface operations with command-line or code-based actions. ## When NOT to use eval-view - If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. - When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. - If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. - If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this. ## When NOT to use WeaveBench - Avoid WeaveBench if your testing needs do not involve scenarios that require the integration of both GUI and CLI operations. - Do not use it when you are specifically interested only in benchmarking agents designed for single-channel tasks, either strictly CLI-based or purely graphical interface-driven. ## Common questions ### What is the difference between eval-view and WeaveBench? eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. WeaveBench: A Long-Horizon Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces. See the comparison table for live GitHub stats and shared categories. ### When should I choose eval-view over WeaveBench? Choose eval-view over WeaveBench when License: eval-view is Apache-2.0, WeaveBench is MIT; Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents; eval-view ships Docker support for self-hosted deployment; When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ### When should I choose WeaveBench over eval-view? Choose WeaveBench over eval-view when License: WeaveBench is MIT, eval-view is Apache-2.0; Tags unique to WeaveBench: agent-as-judge, benchmark, computer-use-agent, gui-agent; Use WeaveBench if you need to assess agents capable of handling tasks that require intermingling graphical user interface operations with command-line or code-based actions. ### When should I avoid eval-view? If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this. ### When should I avoid WeaveBench? Avoid WeaveBench if your testing needs do not involve scenarios that require the integration of both GUI and CLI operations. Do not use it when you are specifically interested only in benchmarking agents designed for single-channel tasks, either strictly CLI-based or purely graphical interface-driven. ### Is eval-view or WeaveBench more popular on GitHub? WeaveBench has more GitHub stars (167 vs 134). Stars measure visibility, not whether either tool fits your constraints. ### Are eval-view and WeaveBench open source? Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, WeaveBench: MIT). ### Where can I find alternatives to eval-view or WeaveBench? GraphCanon lists graph-backed alternatives at [eval-view alternatives](/tools/hidai25-eval-view/alternatives) and [WeaveBench alternatives](/tools/weavebench-weavebench/alternatives) ([eval-view markdown twin](/tools/hidai25-eval-view/alternatives.md), [WeaveBench markdown twin](/tools/weavebench-weavebench/alternatives.md)), 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](/compare/hidai25-eval-view-vs-weavebench-weavebench.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, eval-view or WeaveBench? eval-view: Active. WeaveBench: 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 eval-view and WeaveBench? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [eval-view trust report](/tools/hidai25-eval-view/trust); [WeaveBench trust report](/tools/weavebench-weavebench/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hidai25-eval-view`](/api/graphcanon/graph?tool=hidai25-eval-view) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_