Qodo pricing in 2026: trial, Pro Team, and Enterprise plans.

The published plans

The Qodo pricing page (qodo.ai/pricing) and the vendor documentation (docs.qodo.ai/pricing-and-usage) describe a 14-day free trial plus two paid arrangements: a self-serve Pro Team plan and a custom Enterprise plan (checked July 2026). This is a change from the earlier Free / Teams / Enterprise per-seat structure the product carried under the Codium brand. There is no longer a perpetual free tier on the current pricing page; the trial gives new workspaces unlimited usage for two weeks before a paid plan is required.

The paid plans are usage-based, not seat-based. The vendor doc states billing is metered on credits with "unlimited users per workspace" rather than a fixed per-user charge. Enterprise adds single-sign-on, self-hosted and dedicated deployment options, custom contracts, and dedicated support. The exact credit allocation and per-credit rate sit on the live vendor page and have changed several times since the brand transition; this site does not pin a current rate because it moves faster than this page can be re-verified.

How the credit model works

Qodo meters usage in credits drawn from a monthly pool that renews on a billing cycle. Per the vendor documentation, each action consumes credits: test generation, code review, and IDE or CLI calls all draw from the same pool, and premium models cost more credits per call than standard ones. Usage beyond the included pool is billed as overage at the same per-credit rate as the base plan, so there is no hard cap that stops work mid-sprint, but there is a variable line item that scales with how heavily the team leans on the tool.

The practical implication for budgeting: a team cannot forecast Qodo cost from headcount alone. Two teams of the same size can consume very different credit volumes depending on how many tests they generate, how often the CLI runs in CI, and whether they route to premium or standard models. Estimate expected credit consumption per engineer per month, then apply the current per-credit rate from the live page, then add headroom for the premium-model share creeping up as adoption deepens.

What is generated

Qodo Cover produces framework-native unit tests in the source language (Jest for JavaScript and TypeScript, pytest for Python, JUnit for Java, NUnit for C#, and others). The tests slot into the existing test runner; no special infrastructure is required to run them. The model uses LLM completion against source code with context (existing tests, type signatures, related code) to produce tests that reflect inferred developer intent.

The artefact is the customer's code, in the customer's repository, in the framework the team already uses. This is the structural difference from a managed-service or a platform-bound vendor: there is no lock-in to a proprietary test format. The cost of switching tools is mostly the IDE workflow change rather than a test-artefact migration.

Cost variables

Active engineer count. More engineers generating tests means more credit draw, so cost still tracks team size, but through consumption rather than a fixed per-seat charge. Volume discounts apply through the credit economics at higher usage.

CI usage volume. The CLI runs in CI on every pull request (or nightly, or per merge), consuming credits through the vendor's managed runtime. High-volume CI usage on the Pro Team plan may push the team toward the Enterprise plan where the credit and runtime economics are negotiated.

Self-hosted requirement. Air-gapped deployment or strict code-residency requirements move the conversation to Enterprise where self-hosted and dedicated cloud options are available.

Compliance tier. Single-sign-on, audit logs, and similar enterprise controls are Enterprise-plan features. Buyers with these requirements should expect Enterprise pricing rather than scaling the Pro Team plan up.

Hidden costs

Developer review time. Even with good test generation, the developer who owns the code under test must review the generated tests before merge. The review is fast (often a minute or two per test) but it is not free; for a team generating hundreds of tests per week, the review time compounds.

Onboarding. Adopting an AI test-generation tool takes 2 to 4 weeks of cultural adoption: developers learning the prompts, the team agreeing on review conventions, the CI integration being tuned. This is real engineering time that is not on the Qodo invoice.

Model freshness. LLM-driven tools see meaningful capability changes as underlying models update. A team locked into a contract that does not include model upgrades may pay for a less capable product six months later. Confirm the model-update policy as part of procurement.

How Qodo compares

The most common comparison is Qodo against Diffblue Cover. The structural difference is technique (LLM completion vs RL search) and scope (polyglot vs JVM-only). For a polyglot codebase, Qodo is the obvious fit because Diffblue is out of scope. For a JVM-only codebase, both are in scope and the choice depends on the technique trade-off; see Diffblue vs Qodo Cover for the head-to-head.

Qodo also competes with GitHub Copilot for test generation. Copilot is per-user, IDE-integrated, and well-known; Qodo is specifically focused on test generation as a primary use case and produces a deeper artefact. Teams that already pay for Copilot for general code completion sometimes find that Copilot's test-generation capability is adequate and Qodo's incremental value does not justify the added credit spend. The honest test is a side-by-side pilot on the team's real modules.

Procurement framing

The 14-day trial removes a meaningful adoption barrier compared with contact-sales-only vendors. A team can pilot Qodo without procurement involvement, validate the workflow on real code, and then make a defensible case for the Pro Team or Enterprise plan. This is structurally easier than the all-or-nothing enterprise contracts that Diffblue and similar vendors require, though the trade-off is that the trial is time-boxed rather than a standing free tier.

For teams ready to procure: walk into the conversation with active engineer count, expected credit consumption, CI usage estimate, compliance posture, and the alternatives being evaluated. The Enterprise plan rates respond to competitive context like any other enterprise tool.

Frequently asked questions

Is Qodo the same as Codium?

Qodo is the current brand. The product was previously named Codium and the IDE plugin still carries some legacy naming. The vendor consolidated the brand under Qodo and the pricing page is now at qodo.ai/pricing.

Does Qodo work in CI?

Yes. The Pro Team and Enterprise plans include CI integration via the qodo-cover CLI; tests can be generated and updated as part of a pull-request workflow. The IDE delivery is the more visible surface but the CLI is the workflow that scales across the team.

Is Qodo free?

As of July 2026 Qodo's pricing page centres on a 14-day free trial rather than a perpetual free tier: every new workspace gets unlimited usage for two weeks, after which a paid plan is required. This is a change from the earlier model that carried a standing free tier, so a buyer expecting a permanent free plan should budget for a paid Pro Team plan after evaluation.

How do Qodo credits work?

Qodo's paid plans are usage-based rather than seat-based: the vendor documentation describes a credit pool that renews monthly, with each action (test generation, review, IDE and CLI calls) drawing credits and premium models drawing more than standard ones. Usage beyond the included pool is billed as overage at the same per-credit rate. Budget on expected credit consumption per engineer per month, not on a flat per-seat figure.

Self-hosted available?

Enterprise tier includes self-hosted and dedicated deployment options. The default is cloud SaaS. Buyers with code residency requirements should request the architecture detail in the procurement conversation.

Can I switch between Qodo and Diffblue mid-year?

Technically yes; the artefacts are framework-native tests that live in the customer's codebase. The friction is operational (different IDE workflows, different developer habits, different test-quality profiles) rather than contractual. Most teams that pilot both commit to one for at least a year before re-evaluating.