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Head to head · Verified 2026-08-11

Cubic vs Kodus

Cubic covers more of the baseline (7.5/9 vs 6.5/9), but the split matters more than the total. Everything below comes from each vendor's public documentation, mapped against the same 9 standards.

Cubic

AI PR Review

AI code review for GitHub PRs plus scheduled whole-codebase bug scans, with local CLI review, custom agents, and issue checks.

7.5/9 Coverage score 7.5 out of 9
Licence
Proprietary
Self-hosting
Unknown
From
$30/dev/mo

Kodus

AI PR Review

Open-source AI code review built to run where the organization controls: self-hosted or cloud, models under your keys, org-wide Kody Rules.

6.5/9 Coverage score 6.5 out of 9
Licence
Open source
Self-hosting
Self-hostable
From
$10/dev/mo

The short answer

Across the 9 standards, Cubic is better documented on 3 (local and PR review, actionable fixes and ROI reporting), Kodus on 2 (sandbox validation and cost control), and 4 come out even.

On deployment they are not interchangeable: Cubic is undocumented on self-hosting, while Kodus is fully self-hostable on a standard plan. If code cannot leave your network, that single row decides the evaluation before anything else on this page.

Kodus publishes its source under AGPL-3.0 (dual-licensed; enterprise-marked files commercial); Cubic is proprietary. That changes what you can audit, fork, and keep running if the vendor's terms change.

Pick Cubic if you care most about local and PR review, actionable fixes and ROI reporting.

Pick Kodus if you care most about sandbox validation and cost control, the reviewer has to run inside your own infrastructure and you want to read the source before you trust it.

Side by side

Fact Cubic Kodus
Licensing Proprietary Open source — AGPL-3.0 (dual-licensed; enterprise-marked files commercial)
Self-hosting Unknown Yes — full stack
Free tier Limited free tier Limited free tier
Pricing Free: 20 PR reviews/mo; Team $30/dev/mo annual ($40 monthly); Pro $79/dev/mo annual ($99 monthly); Enterprise custom. Free for OSS teams Free Community cloud tier (BYOK, up to 10 Kody Rules); Teams $10/dev/mo + your token costs; Enterprise custom; self-hosting free under AGPL
Model control Fixed vendor models (OpenAI, Anthropic); BYOK listed only as an Enterprise plan feature BYOK on every plan: OpenAI, Anthropic, Gemini, Vertex, Novita, or any OpenAI-compatible endpoint (vLLM/Ollama); zero token markup
Platforms GitHub GitHub, GitLab, Bitbucket, Azure DevOps, Forgejo
Last verified 2026-08-11 2026-08-11

marks a row where the two genuinely differ.

All 9 standards

✓ documented · ~ partial · ✗ not offered · ? undocumented. The arrow marks which tool documents more on that standard — it is not a quality judgement, only a coverage one.

Cubic: AI wiki indexes the repo; cross-repo reviews can read up to 5 linked repositories during PR review.

Kodus: Repo-level analysis plus linked sibling repos; pulls business context from Jira, Linear, and Notion.

Cubic: cubic.yaml custom agents with sensitivity levels and ignore filters; docs promise minimal verbosity.

Kodus: Plain-language Kody Rules with global-repo-directory scope; auto-imports .cursorrules, CLAUDE.md, AGENTS.md, etc.

Cubic: Local CLI review before pushing, IDE/agent setup (Cursor, VS Code, Claude Code), and an MCP server.

~

Kodus: Reviews run via CLI locally, in CI, and on PRs; distinct local-vs-PR behavior modes not detailed publicly.

Cubic: Checks PRs against linked Linear/Jira issue requirements, posting a done/missing table in the review.

Kodus: Pulls context from Jira, Linear, and Notion to check a PR against what the ticket asked for.

Cubic: Thumbs up/down calibrate per-codebase noise; typed replies are remembered; learnings visible in settings.

Kodus: Kody generates rules automatically by analyzing team review history; rules and review history persist.

?

Cubic: No documented code execution, test runs, or preview-environment validation.

Kodus: No documented sandbox execution or runtime validation of findings.

~

Cubic: BYOK gated to Enterprise; per-seat pricing with LOC quotas and flex top-ups; no token-cost visibility.

Kodus: BYOK on every plan, zero token markup, published cost estimates, token-usage dashboard.

Actionability Cubic ↑

Cubic: 'Fix with cubic' background agents generate and apply fixes; Pro adds auto-created fix PRs.

~

Kodus: Provides fix suggestions in reviews; one-click commit flow not verified in the posts we checked.

Cubic: Review, delivery, and authorship dashboards incl. cycle-time and merge-time trends; no cost-per-PR telemetry.

~

Kodus: Token-cost and usage dashboard documented; DORA-style ROI reporting not verified in public posts.

Cubic vs Kodus: FAQ

What is the main difference between Cubic and Kodus?

Cubic covers more of the baseline (7.5/9 vs 6.5/9), but the split matters more than the total. Cubic is undocumented on self-hosting and proprietary; Kodus is fully self-hostable on a standard plan and open source under AGPL-3.0 (dual-licensed; enterprise-marked files commercial).

Is Cubic cheaper than Kodus?

Cubic starts at $30/dev/mo and Kodus at $10/dev/mo, as published by each vendor on 2026-08-11 and 2026-08-11. Compare total cost rather than seat price: Cubic bills models as fixed vendor models (openai, anthropic); byok listed only as an enterprise plan feature, Kodus as byok on every plan: openai, anthropic, gemini, vertex, novita, or any openai-compatible endpoint (vllm/ollama); zero token markup.

Can Cubic and Kodus be self-hosted?

Cubic: Unknown — No self-hosted or VPC deployment published; Enterprise details gated behind a demo (lists GitHub Enterprise support only). Kodus: Yes — full stack — Free under AGPL via Docker Compose, VM, or Kubernetes/Helm; no seat minimums; optional daily heartbeat can be disabled.

Do Cubic and Kodus support the same platforms?

Both document support for GitHub. Cubic additionally documents nothing else; Kodus adds GitLab, Bitbucket, Azure DevOps and Forgejo.

Which one scores higher against the 9-pillar standard?

Cubic scores 7.5/9 against 6.5/9. The score is coverage of documented capability, not quality of findings — the full formula is on the methodology page.

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