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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →IBM Bob, Continue, and Tabby all support self-hosted or local AI coding workflows, but they are not equivalent deployment choices. Bob is a backend platform deployed on customer-operated OpenShift; Continue is an IDE extension that can connect to local, self-hosted, or hosted model endpoints; Tabby describes itself as a self-hosted, open-source assistant, but the available project information here is not detailed enough to verify its production requirements feature by feature.
The practical choice depends on where inference and development context travel, what infrastructure your team already operates, and who owns identity, certificates, updates, monitoring, and support. This comparison reflects documentation checked October 4, 2026—not hands-on testing.
How the three deployment models differ
| Option | What you deploy or configure | Operational ownership | What the available documentation establishes |
|---|---|---|---|
| IBM Bob | A backend platform on customer-operated Red Hat OpenShift Container Platform, deployed with an operator and Helm charts. Developers use Bob IDE extensions and bob-shell. |
The customer operates the OpenShift environment and handles lifecycle, networking, storage, identity, and platform security-event logging and monitoring. | Documented connected and air-gapped deployment paths, prerequisites, model connections, and client certificate requirements. |
| Continue | An IDE extension with local configuration that specifies models and endpoints. Models may be local, self-hosted, or hosted. | If using self-hosted inference, the team operates the model-serving layer and configures the endpoint; users or administrators maintain client configuration. | An official offline setup using a downloaded VSIX, disabled anonymous telemetry, and a local model; endpoint configuration and provider options are documented. |
| Tabby | The project identifies itself as a self-hosted, open-source AI coding assistant. | The exact production responsibility split is not established by the project README reviewed here. | The self-hosted and open-source positioning is established; detailed current deployment, offline, model, identity, and support requirements are not established by that source. |
These distinctions matter: hosting an IDE client locally does not by itself keep inference traffic on premises, and a self-hosted label does not prove an air-gapped procedure or define who operates every component.
IBM Bob: a managed application backend on your OpenShift
IBM’s self-hosted overview describes Bob as a customer-managed deployment on OpenShift Container Platform. Its backend services, infrastructure, and integrations run inside the organization’s environment. IBM says a dedicated cluster is not required, but the cluster must have sufficient compute, memory, and storage. Deployment uses the Bob Kubernetes Operator and Helm charts; the customer owns the platform lifecycle and related operational controls.
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Prerequisites and deployment work
The current prerequisites page specifies OpenShift Container Platform 4.20 minimum, Helm 3.14.0 or later, an entitled IBM release bundle, IBM Entitled Container Registry access, an administrative workstation, and model endpoints. The installation overview says cluster-admin privileges are required for the cluster administrator. Check these requirements against the release you plan to deploy; platform versions and prerequisites can change.
IBM’s installation overview states: “The installation is performed using the bobctl command-line interface.” The installation process includes configuring model connections and identity. Bob clients also require a trusted certificate for the service endpoint, so plan certificate authority distribution and client trust as part of rollout—not as an afterthought. See IBM’s configuration documentation and access instructions.
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Connected versus air-gapped installation
IBM documents connected installation that can use hosted or on-premises inference. Its air-gapped methods use on-premises inference only. Telemetry is enabled by default in connected deployment and disabled by default in the two documented air-gapped paths; review the selected release’s settings and network behavior before deployment. See IBM’s installation instructions.
IBM’s October 1, 2026 release post says Bob self-hosted became generally available on September 24, 2026. It describes model choice as a frontier model from a cloud service the organization already uses or an open-weight model running on its own GPUs. Access is sales-led through IBM or a Business Partner. Confirm licensing, entitlement, supported models, and commercial terms directly with IBM; pricing is not established here.
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Continue: an IDE client whose endpoint determines where inference runs
Continue is a configurable IDE extension rather than, by itself, a centrally deployed inference backend. Its self-host-a-model guide and provider overview describe endpoint options including Ollama and OpenAI-compatible services, along with authentication headers and certificate configuration for private endpoints.
In practice, teams must select and operate the model-serving layer for the workflows they want—such as chat, editing, autocomplete, embeddings, or agent tasks—and set each model role to the intended endpoint. Continue’s provider documentation includes local, self-hosted, and hosted services. Choosing Continue alone therefore does not ensure all inference requests stay on premises; verify the configured endpoints and network routes for each role.
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Offline setup
Continue’s official guide, “How to Run Continue Without Internet”, describes three key steps: install the VS Code extension from a downloaded VSIX, turn off “Allow Anonymous Telemetry,” and configure a local model, then restart VS Code. This is a documented offline recipe, not a guarantee that every model, workflow, or configuration will work without internet access.
Local configuration and Hub configuration
Continue documents both a local configuration path stored on the developer’s machine and a Hub configuration path managed through Mission Control. The configuration guide explains the distinction. Teams with strict control requirements should evaluate the local configuration and model route alongside any centralized management they intend to use; they should not assume that those paths have identical data handling or administration implications. Formal private-deployment products and current commercial terms are not established here.
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Tabby: promising self-hosted positioning, but verify deployment details
The Tabby project README calls Tabby a “self-hosted AI coding assistant” and an open-source, on-premises alternative to GitHub Copilot. That is enough to put it on a shortlist for teams exploring self-hosted projects, but not enough to compare it responsibly with Bob or Continue on operational specifics.
The README reviewed here does not establish current hardware requirements, supported identity features, exact offline behavior, model compatibility, licensing terms, or enterprise support. Before a production decision, check Tabby’s current official documentation and release-specific installation instructions against your requirements.
Choose based on traffic boundaries and operating ownership
- Consider IBM Bob if your organization operates supported OpenShift and wants an enterprise backend administered within its environment. Account for platform staffing, identity and certificate setup, model endpoints, and the entitlement and sales-led access process.
- Consider Continue if you want a configurable IDE client and are prepared to choose and operate—or deliberately use—a model endpoint for each workflow. Its offline path is documented, but endpoint and telemetry settings still matter.
- Evaluate Tabby further if an open-source, self-hosted project is appealing, but make the production choice only after verifying current deployment, security, compatibility, licensing, and support details in its official release documentation.
For any option, map the path taken by IDE traffic, prompts and code context, inference requests, logs, telemetry, identity data, model-provider traffic, and update downloads. On-premises deployment does not automatically establish privacy or compliance. IBM explicitly assigns platform security logging and monitoring to the OpenShift operator/customer, while Continue’s offline guide explicitly instructs users to disable anonymous telemetry. Validate actual network behavior and policy against the exact version and configuration you intend to use.
What to confirm before a pilot or procurement decision
- Define the boundary. Decide whether “on premises” means the application backend, the model inference service, the IDE configuration, or all of them. Identify which data may leave the organization.
- Map the infrastructure owner. Confirm who will run the OpenShift platform, model-serving infrastructure, client configuration, certificates, identity integration, monitoring, and upgrades.
- Test the required network mode. For an air gap, verify extension or client distribution, model availability, registry or package access, telemetry settings, and update procedures for the exact deployment route.
- Validate workflow-model fit. Check model compatibility and endpoint configuration for each needed capability rather than assuming one model or provider supports every feature.
- Confirm commercial and support terms. For Bob, verify IBM entitlement, supported release, and procurement terms. For Continue and Tabby, verify current product, licensing, and support terms directly; the documentation reviewed here does not establish a comparable commercial package for either.
No comparative performance benchmark or independent head-to-head statistic is established by the documentation cited here. Treat selection as an architecture, governance, and operations decision first, then assess quality and performance in a pilot using your own codebase and workflows.
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