Inference platform comparison

KeepRouter vs Together AI: model access or open-weight deployment

KeepRouter is a managed, prepaid catalog for supported models from several makers, with published customer routes and prices. Together AI focuses on serving open-weight models through serverless and dedicated inference, and also offers a training path. Choose by required model, deployment control, billing account and workload, then test the exact route rather than assuming the shared OpenAI client shape makes responses equivalent. [1] [2] [4] [6]

Last reviewed 2026-09-29 · Editorial review: KeepRouter Editorial

Short answer

Choose KeepRouter if the listed model and endpoint already fit your application and you want a managed prepaid account without operating a model deployment. Choose Together AI if your main requirement is serving an open-weight model on its serverless fleet, moving it to reserved compute, or training and deploying a custom variant. Together's serverless overview, dedicated inference description and fine-tuning page describe those paths. Neither product's OpenAI-shaped example proves that every tool, streaming event, context rule or model revision is portable.

Decision table

Decision	KeepRouter	Together AI
Main job	Managed access to the currently published multi-maker catalog	Serve and customize open-weight models
First route	Exact model endpoint in the live catalog	Together serverless model endpoint and ID
Customer billing	KeepRouter prepaid balance and published customer rates	Together account and its current serverless or dedicated pricing
Dedicated compute	No customer deployment product in the public API	Documented dedicated model endpoint with reserved compute
Custom model path	Not a public KeepRouter route	Together training and dedicated deployment path
Operational owner	KeepRouter runs upstream routing; customer owns application behavior	Together runs inference; customer selects serving tier and model configuration

This is a fit comparison, not a speed or price ranking. Together's pricing page describes different charges for serverless and dedicated paths, while KeepRouter's catalog publishes prices by model and billing unit. Compare the same exact model revision, input/output sizes, cache behavior, region and concurrency before using either list price in a budget.

When Together AI is the stronger fit

Use Together when the product depends on a particular open-weight model or a tuned variant and you want a path from token-billed serverless testing to reserved GPUs. That transition changes capacity and commercial responsibility. It should be decided from measured throughput, p95 latency, utilization and all idle time, not from a single token price. If you need Together-only training or deployment controls, a general managed catalog cannot replace them.

When KeepRouter is the stronger fit

Use KeepRouter when you need the specific routes visible in its public OpenAPI and catalog, a prepaid customer balance, scoped keys and request-level usage for an application that tests several model makers. The application still validates model quality and owns retry, fallback and tool semantics. KeepRouter does not expose Together's reserved GPU configuration as a customer control; do not mistake a shared client library for shared infrastructure.

Decide whether dedicated capacity is solving a measured problem

For a bursty prototype, record peak concurrency and idle periods before pricing dedicated capacity. For a steady workload, measure the throughput and latency required at the chosen model configuration. Together’s dedicated inference offering is a serving option to evaluate against those requirements. KeepRouter supplies catalog API access; it is not a reservation of a dedicated deployment. Compare cost at both your expected utilization and a quieter month instead of assuming every provisioned hour is useful.

Migration proof, not a base-URL claim

Export one representative request and write down the old model ID, system messages, tools, expected stream termination, error mapping and billing fields. Choose an exact candidate on the target service. Run plain text, a long-context case, a tool round trip, a 429 and a timeout. Record the final answer, request IDs, usage, charge, p50/p95 latency and failure handling. The API migration checklist and gateway evaluation framework provide reusable test sheets. Keep the former route available until the new one passes the application-level tests.

For teams whose only requirement is access to a broader inference ecosystem, also compare Fireworks AI and the OpenRouter alternatives guide. The right choice may be a split: KeepRouter for listed multi-maker workloads and Together direct for custom open-weight serving.

Frequently asked questions

Is Together AI just another gateway?

No. Its official offering includes serverless inference, dedicated model serving and training for open-weight models; compare deployment ownership as well as API shape.

Can I move a Together custom model into KeepRouter by changing a URL?

No. Only models and endpoints in the current KeepRouter catalog are published routes; custom weights need their own serving plan.

Does OpenAI compatibility guarantee identical tools?

No. Test the exact model and endpoint with a complete tool round trip, stream, errors and usage fields.

How should dedicated compute be compared with token billing?

Measure utilization, idle time, throughput and p95 latency on the same workload, then include model quality and operations in the total cost.

Sources reviewed

Sources last reviewed 2026-09-28