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Agent-QA vs OpenCode

Bottom line

Agent-QA has a free plan plus paid upgrades, while OpenCode is free.

Which one should you try?

Agent-QA

Freemium

Best for Teams building web and mobile applications

Visit Agent-QA See full review

OpenCode

Free

Best for Developers who want an open-source coding agent in the terminal

Visit OpenCode See full review

Pricing, capabilities and platforms side by side. Prices are as of the "Pricing checked" date in the table.

Agent-QA

Agent-QA

The tool lets you write test steps in plain language — 'Click on the Create issue icon', 'Verify that the created issue is shown' — and an agent translates those into browser actions at runtime, reading visible labels and screen state instead of fragile CSS selectors. After each run, it builds execution memory: observations about navigation contracts, UI quirks, and previously healed steps, which get injected into future runs so the agent stops rediscovering the same UI patterns. Self-healing means that when a component shifts, the agent iterates through recovery attempts rather than failing immediately. The ceiling appears when test logic branches on conditional application state — the YAML authoring model is built for linear flows, and complex branching sends teams back to scripting.

OpenCode

OpenCode

OpenCode is an MIT-licensed AI coding agent for the terminal that works with the model provider you choose, including local models. We installed it and ran three agent tasks: 9 of 9 passed with Claude Opus 5.5, 3 of 9 with a 3B local model.

AttributeAgent-QAOpenCode
PricingFreemiumFree
Price—Free (MIT). Optional Zen models pay as you go; Go $10/mo, Go Plus $40/mo
Pricing checkedNot checked yetOct 19, 2026
Free trialNot statedNot stated
Open sourceYesYes
Has APIYesYes
Self-hosted optionYesYes
PlatformsWeb and mobile (Chromium, mobile drivers)Terminal, Desktop (beta macOS/Windows/Linux), IDE extension
Pros
  • Natural language test authoring against visible UI labels rather than DOM selectors, so a component rename or layout shift does not immediately break the test suite the way a hard-coded selector would.
  • Execution memory that accumulates across runs with trust scores and confirmation counts, which means the agent stops wasting run time rediscovering navigation patterns it has already mapped — later assertions stay focused on actual page behavior.
  • Self-healing iteration within a single run — when an action fails, the agent retries with updated screen state observation rather than failing the step immediately, so transient UI delays cause fewer false negatives.
  • Support for custom and open-source LLM models at the infrastructure level, so teams with data-residency requirements or API cost constraints can run inference locally without forking the tool.
  • Open-source codebase with self-hosted deployment option, which means teams are not locked into a vendor's uptime or data pipeline when running tests against internal staging environments.
  • Passed all 9 of our agent tasks with Claude Opus 5.5.
  • Works with the provider you choose, including a local model behind an OpenAI-compatible server.
  • Open source under the MIT license.
Cons
  • The YAML step format is built for linear flows — action, verify, action, verify. Test scenarios that branch based on runtime application state (for example, different assertion paths depending on what a previous step returned from the server) have no native expression in the authoring model. Teams with conditional logic either maintain a parallel scripting layer or restructure tests into multiple flat suites, which defeats the maintenance advantage.
  • Execution memory is only as reliable as the trust scores the agent has accumulated. On a new application or after a major redesign, early runs produce low-confidence observations and the agent behaves closer to a first-run tool — the adaptive advantage appears after repeated runs against a stable-ish UI, not on day one.
  • Teams whose test requirements outgrow linear natural-language flows — particularly those already running Playwright or Cypress suites with custom fixtures, parameterized data, and programmatic assertions — will find agent-qa's authoring model too constrained and switch back to code-first frameworks where branching logic is a function call, not a workaround.
  • With a 3B local model it passed 3 of 9 tasks (only the simplest one), so plan on a larger model.
  • It reaches out to models.opencode.ai and registry.npmjs.org, and downloads provider packages on first use, so offline setups need those pre-installed.
  • The vendor lists its desktop app as beta.

Made up your mind?

Agent-QA

Freemium

Best for Teams building web and mobile applications

Visit Agent-QA See full review

OpenCode

Free

Best for Developers who want an open-source coding agent in the terminal

Visit OpenCode See full review

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Free trials & curated lists

Specs come from each tool's own site and docs (how we test). AIDiveForge is editorially independent.

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