OpenLuxOpenLux vs Requesty: which managed LLM gateway is the better fit?
Choose Requesty if advanced routing controls, team-level policies and a 600+ model marketplace are central to your AI platform. Choose OpenLux if you want a smaller curated catalogue, transparent per-model rates and a direct OpenAI-compatible path to one unified bill. Both are managed gateways, so the decision turns on control, breadth and operating overhead.
Reviewed by OpenLux Engineering Team · Last verified
OpenLux vs Requesty at a glance
Requesty positions around routing, caching, fallbacks and team control. OpenLux positions around a focused OpenAI-compatible catalogue with visible model rates.
| Decision | OpenLux | Requesty |
|---|---|---|
| Best fit | A managed production catalogue with simple migration and transparent model-level cost | Teams that need deeper routing policy, caching and multi-team gateway controls |
| Catalogue | 19 production models across text, media and retrieval | A 600+ model marketplace according to its current public pricing page |
| Pricing | Published USD rate per model; pay-as-you-go or monthly/yearly plan | Free-model allowance plus pay-as-you-go with a published provider-rate markup; verify current terms |
| Routing | Managed multi-route scheduling and retries inside the OpenLux catalogue | Routing, caching, fallback and team-policy features are a central part of the product |
| Data residency | Global service; enterprise procurement can discuss dedicated routes and contracts | Public materials foreground EU data residency and routing options |
| Setup | One OpenAI-compatible endpoint; create a key and call a catalogue model | Create an account, configure the chosen gateway controls and route traffic |
| Best decision criterion | How quickly can the team operate a shortlist with clear unit economics? | How much routing and policy control does the application actually need? |
What is Requesty best known for?
Requesty describes its managed gateway around routing, caching, fallbacks, EU data residency and team controls. Its public pricing page lists free usage on free models, pay-as-you-go access and enterprise capabilities such as SSO and RBAC. That makes it a plausible fit when the gateway itself is a major part of the AI platform.
A wider catalogue and granular routing can justify a more involved setup. Teams should still validate the exact models, policies and price markup required for their production workload rather than adopting every gateway feature because it is available.
What does OpenLux prioritise instead?
OpenLux narrows the product surface to a 19-model catalogue and an OpenAI-compatible API. The key design decision is that the same endpoint, key and billing account cover text, image, video, audio and retrieval models that are listed publicly with their rates.
That makes OpenLux easier for teams that already know which model families they need. The trade-off is intentional: OpenLux has fewer advanced routing controls and a much smaller catalogue than a marketplace-first gateway. It is a managed aggregator and billing layer, not a self-hosted routing framework or a user-facing model discovery product.
How do routing and reliability requirements change the answer?
If an application needs user-authored routing rules, provider preferences per tenant, response caching policies or separate governance for many teams, evaluate Requesty's documented controls first. A generic OpenAI-compatible endpoint is not enough when routing policy is part of the product.
If the application needs reliable access to a defined model shortlist with automatic retries, regional routing managed by the provider and request-level logs, OpenLux reduces configuration surface. Fewer knobs are an advantage only when they still satisfy the operational requirement, so write down the must-have controls before comparing the products.
How should buyers compare the total price?
Requesty publicly describes a percentage markup on provider rates, while OpenLux publishes a per-model USD rate in its catalogue. Those are different pricing interfaces and can produce a different result depending on the model and volume. Use the exact model identifiers and token mix your application will run.
Include failure cost, engineering time, reconciliation and the value of gateway features in the comparison. A lower raw markup loses if it requires maintaining a complex router, while a richer control plane is unnecessary if nobody will operate it. The right answer is workload-specific.
Can a team migrate from Requesty to OpenLux?
For standard chat-completion calls that use an OpenAI-compatible route, migrate by changing base_url, API key and model identifier. Remove Requesty-only routing, cache or fallback fields from the request before testing. Those features should be replaced only after the team decides whether application code, OpenLux routing or another layer will own them.
Use shadow traffic for representative prompts, compare outputs and error rates, and keep a rollback path through environment variables. Do not migrate a workflow that depends on a unique routing policy until that policy has an explicit replacement.
When is Requesty the better choice?
Choose Requesty when centralised routing policies, broad model discovery, team-level controls and EU routing are buying requirements. Its larger catalogue and feature depth are material advantages for platform teams that need to expose many models and policies to internal users.
Choose OpenLux when the team needs a managed, well-defined model shortlist more than it needs a gateway control plane. OpenLux's smaller catalogue and simpler product surface are the right trade-off when fast onboarding and transparent model-level metering carry more value.
Which option fits?
Choose OpenLux when
- The required models fit a curated production catalogue.
- Published per-model rates and unified USD billing simplify procurement.
- The team wants fewer gateway controls to configure and maintain.
Choose Requesty when
- Routing policies, caching, fallbacks and team governance are product requirements.
- The application needs a very broad model marketplace.
- EU routing and enterprise controls are explicit buying criteria.
Key takeaways
- Requesty is the stronger fit for routing depth and a very broad model marketplace.
- OpenLux is the simpler managed path when a curated catalogue covers the workload.
- Compare the delivered price at the model and volume you actually use.
Frequently asked questions
Is OpenLux cheaper than Requesty?
Not universally. Requesty publishes a provider-rate markup while OpenLux publishes per-model USD rates. Replay a representative workload and include retries, media requests and operational time.
Does Requesty have more models?
Requesty's public pricing page advertises 600+ models. OpenLux publishes a curated catalogue, so the comparison should start with the exact models required by the application.
Which gateway has more routing controls?
Requesty foregrounds routing, caching, fallbacks and team policy controls. OpenLux provides managed routing and retries but does not position itself as a user-authored routing control plane.
Can I use the OpenAI SDK with both?
Yes. Both products expose OpenAI-compatible access for supported models, but platform-specific request fields and model identifiers can differ.
Sources and methodology
Competitor claims were checked against the linked public pages on the verification date. Pricing and product terms can change; confirm them before purchase.
- Requesty pricingPublic plans, model count and gateway claims checked 2026-10-30.
- Requesty LLM gateway alternativesVendor-authored comparison and methodology context.
- OpenLux model catalogue and ratesChecked alongside the 19-model catalogue on 2026-10-30.
- OpenLux pricingPay-as-you-go metering and subscription terms.
Test the simpler managed path
Use one OpenLux key to replay a representative workload and measure the delivered cost.