Separate the model requirement from the hosting preference
Self-hosting gives your team responsibility for the serving stack, capacity, updates and availability. It can be appropriate for custom weights or infrastructure constraints that an API service does not address.
It also limits model choice to models you can obtain and operate. A proprietary model available only as a service cannot become self-hosted simply because the application uses a common API format.
Use API access for a wider model shortlist
TextCortex brings GPT, Claude and Gemini together with Kimi, GLM, DeepSeek and MiMo behind one integration. Your application can select different models without deploying a separate serving stack for each.
For EU inference, use an eligible EU-hosted route. Managed hosting still needs a clear processing arrangement, but the application team does not have to provision the model’s GPU infrastructure.
Include operating work in the comparison
Compare the same workload and reliability target on both options.
- Capacity planning and idle resources.
- Serving updates, model rollout and rollback.
- Request limits, monitoring and incident response.
- Required model quality and proprietary-model access.
- Engineering time as well as usage charges.
A hybrid architecture can be deliberate
An application can retain a specialized self-hosted model while using an API for other tasks. Keep the routing decisions explicit and measure both paths using the same task outcomes.
Explore the TextCortex model API and routing guide to decide which workloads belong on each path.