Self-hosting AI code review has no single price: budget for the review application, a host, model inference, storage and backups, and the work of operating the service. Hosting the application yourself does not necessarily keep code in your environment or make AI calls free; those depend on where the model runs.
What makes up the monthly cost?
Estimate a monthly total using costs your team will actually incur. Include one-time setup or hardware purchases as an explicitly allocated monthly amount if you want to compare them with recurring subscriptions.
As an Amazon Associate I earn from qualifying purchases.
| Cost line | What to include | What is established |
|---|---|---|
| Application license | License obligations, and any paid enterprise license or support your requirements call for. | Kodus Community is offered under AGPLv3; Kodus Enterprise adds SSO, role-based access, and audit logs. An Enterprise price is not stated in its documentation. |
| Host and storage | Compute, disk, backups, network, monitoring, and any redundancy you need. | Kodus documents an 8 GB RAM minimum and recommends 16 GB for repositories over 100,000 lines. It does not establish a cloud-hosting price. Kodus documentation |
| Model inference | Hosted-model usage charges, or the cost of local serving capacity, including capacity that sits idle. | Kodus and PR-Agent document external model options as well as customer-operated endpoints; neither source establishes a workload-based monthly rate. Kodus documentation PR-Agent README |
| Operations | Setup, upgrades, secret management, webhook maintenance, logs, access controls, and incident response. | Kodus estimates 15–30 minutes for a first installation. That is the vendor’s install estimate, not a production deployment or ongoing maintenance estimate. Kodus documentation |
| Security and compliance | Identity controls, audit retention, private networking, and any image-mirroring or isolation work you require. | Kodus describes SSO, role-based access, and audit logs as Enterprise features; its documentation says air-gapped deployments require customer-managed image mirroring. Kodus documentation |
A practical model is monthly total = license + host and storage + inference + operations labor + security and compliance. Record each item as recurring or one-time, and distinguish cash expenses from staff time. For a useful estimate, also record monthly pull-request count, typical diff size, model and context size, caching, concurrency, host geography, and backup requirements. Without those workload details, a universal API-versus-local cost comparison is not supported.
Recommended Free Tools
Where does the model run?
Self-hosting the review application and self-hosting the AI model are separate decisions. Kodus can call external providers or use a customer-operated OpenAI-compatible endpoint such as vLLM, Ollama, TGI, or LiteLLM. PR-Agent documents hosted model options and an Ollama setup through LiteLLM. Kodus documentation PR-Agent README
#1 Best Overall
| Operating pattern | Cost and data trade-off | What to compare |
|---|---|---|
| Self-hosted application, external model API | Less model-serving infrastructure to operate, but model usage can remain a recurring charge. Review data sent to the provider is subject to that provider’s data handling. | Per-review usage, data terms, latency, and provider availability. |
| Self-hosted application and local model | Model requests can remain within the team’s network, while cost shifts to suitable compute, power, capacity planning, and serving operations. | Hardware utilization, concurrency, model choice and quality, latency, and maintenance. A host’s application RAM requirement is not a GPU recommendation. |
| Managed SaaS or enterprise deployment | Subscription or contract costs replace some self-operated work, but deployment control, data handling, model choice, and whether on-premises deployment is included vary by offer. | Contract scope, operating effort avoided, deployment options, access controls, and data boundary. Qodo’s enterprise page describes enterprise deployment and model options. |
“Self-hosted” alone does not establish where prompts, diffs, or model requests go. Confirm the application’s configured endpoint and the provider’s data terms before treating a deployment as contained within your environment.
What published figures can—and cannot—tell you
Kodus host and setup figures
Kodus documentation current when accessed in 2026 specifies at least 8 GB RAM for the host, recommends 16 GB for repositories over 100,000 lines, and allocates 4–8 GB to the worker. It also calls for Docker with Compose and a domain or fixed IP for webhooks. These are application deployment details, not local-model GPU sizing or a cloud bill. The same documentation estimates 15–30 minutes for first installation; that vendor estimate does not include a full production rollout or recurring operations. Kodus documentation
A SaaS comparator, not a self-hosting price
An AWS Marketplace listing accessed on October 7, 2026, displays Qodo SaaS at $190 per month for five developers, $1,900 per month for 50 developers, and $240 per month for a 20,000-credit Pro Teams plan. The listing is for SaaS, not self-hosted Qodo, and says additional AWS infrastructure costs may apply. These figures are a dated comparison point, not a market average or a direct quote for running your own service. AWS Marketplace listing
Do these 3 things before closing this tab:
1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesA performance result is not a price estimate
A preliminary paper posted October 11, 2025, reports a median first-feedback time of 59.8 seconds in its offline setup using a single-GPU system. That result describes the paper’s particular system; it does not establish a general hardware prescription, monthly operating cost, or expected latency for another workload. Mandal and Jiang, “Grounded AI for Code Review: Resource-Efficient Large-Model Serving in Enterprise Pipelines”
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to build a defensible estimate
- Define the workload. Count monthly pull requests and estimate typical diff and context sizes. Note peak concurrency and whether reviews run continuously or in batches.
- Choose the model location. Decide whether the application will call an external API or a team-operated endpoint. For an API, use that provider’s current pricing and your expected token usage; for local serving, price the required compute, power, and capacity. No workload-based rate is established by the sources cited here.
- Price the application host separately. Include the VM or owned server, disk, backups, network, and monitoring. For Kodus, use its documented RAM guidance as an application baseline, not as a price quote or GPU specification.
- Check license and controls. Account for open-source license obligations and determine whether your access, audit, or compliance needs require paid features or additional infrastructure.
- Include people and operational work. Estimate setup and recurring hours for upgrades, secrets, webhook exposure, logs, access reviews, and incident handling. Do not substitute a vendor’s first-install estimate for those ongoing tasks.
- Compare on equal terms. Calculate monthly cost at the same PR volume for each option, then compare data boundary, model quality and choice, latency, maintenance burden, and access controls alongside price.
The resulting number is specific to your workload, model, provider, location, and operating requirements. A self-hosted application that uses an external API and a fully local deployment are different budgets, even if they use the same review interface.
Quick Recap
Best Value
Rank #4
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
