Step-by-step guide

How to Migrate from OpenRouter to LLMWise

Go beyond basic model routing with Compare, Blend, Judge, and Mesh modes, plus built-in optimization that learns from your usage data.

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You only pay credits per request. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

First success in 60 seconds
Step 01Sign up in 10 secondsGet 40 free creditsStep 02Open your dashboardCreate API keyStep 03Send first requestRun a sample
Why teams start here first
No monthly subscription
Pay-as-you-go credits
Start with trial credits, then buy only what you consume.
Failover safety
Production-ready routing
Auto fallback across providers when latency, quality, or reliability changes.
Data control
Your policy, your choice
BYOK and zero-retention mode keep training and storage scope explicit.
Single API experience
One key, multi-provider access
Use Chat/Compare/Blend/Judge/Failover from one dashboard.
1

Compare feature sets

OpenRouter provides unified access to many models, but LLMWise adds orchestration layers on top: Compare mode runs prompts on multiple models in parallel, Blend synthesizes a combined response, Judge lets one model evaluate another, and Mesh provides circuit-breaker failover. Map your current OpenRouter usage to identify which LLMWise features fill gaps in your workflow.

2

Swap to LLMWise (SDK or REST)

Keep your prompts and role/content messages, then swap your OpenRouter call site to LLMWise (recommended via the official SDKs). You’ll also need to map model IDs (OpenRouter uses provider/model; LLMWise uses a curated model list).

3

Migrate your routing configuration

Translate any OpenRouter model preferences or fallback settings into LLMWise equivalents. LLMWise model IDs follow a provider/model pattern (e.g., gpt-5.2, claude-sonnet-4.5). If you used OpenRouter's routing parameter, replace it with LLMWise Mesh mode, which offers circuit-breaker-based failover with configurable fallback chains rather than simple ordered lists.

4

Enable advanced orchestration modes

Start using LLMWise-exclusive features. Use Compare to benchmark models on real traffic, Blend to combine the best of multiple model responses, or Judge to have a strong model score weaker candidates. These modes require no additional infrastructure; they are native API endpoints.

5

Activate data-driven optimization

LLMWise Optimization policies analyze your historical request logs and recommend model routing changes based on your goal: balanced performance, lowest cost, lowest latency, or highest reliability. Enable an optimization policy after accumulating a week of traffic, and the platform will suggest primary and fallback models backed by your real-world data.

Evidence snapshot

How to Migrate from OpenRouter to LLMWise execution map

Operational checklist coverage for teams implementing this workflow in production.

Steps
5
ordered implementation actions
Takeaways
3
core principles to retain
FAQs
4
execution concerns answered
Read time
10 min
estimated skim time
Key takeaways
✓Migration from OpenRouter is straightforward: keep your message shape, swap the client call, and map model IDs.
✓LLMWise adds Compare, Blend, Judge, and Mesh orchestration modes that OpenRouter does not offer.
✓Data-driven Optimization policies replace manual model selection with recommendations based on your actual usage patterns.

Common questions

Is LLMWise compatible with the OpenRouter request format?
Your prompts and the role/content message shape migrate cleanly, but LLMWise is not positioned as a base-URL swap for the OpenAI SDK. Use the official LLMWise SDKs (Python/TypeScript) or call POST /api/v1/chat directly.
Does LLMWise support as many models as OpenRouter?
LLMWise curates nine high-quality models from five providers (OpenAI, Anthropic, Google, xAI, DeepSeek) rather than listing hundreds. The focus is on orchestration, failover, and optimization across a vetted set rather than raw model count.
What is the pricing difference between OpenRouter and LLMWise?
LLMWise uses a credit-based system where each mode has a fixed credit cost (chat=1, compare=3, blend=4, judge=5). You can also bring your own API keys to route directly to providers at their native pricing while still using LLMWise orchestration features.
Can I use my OpenRouter API key with LLMWise?
No. LLMWise manages its own provider connections and offers BYOK for individual providers (OpenAI, Anthropic, etc.), not for aggregators. You would add your direct provider keys if you want BYOK routing.

One wallet, enterprise AI controls built in

You only pay credits per request. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

Chat, Compare, Blend, Judge, MeshPolicy routing + replay labFailover without extra subscriptions
Start free with 40 creditsSee pricing examples
Related pages
How to Build a Multi-Model AI ApplicationHow to Compare LLM Models Side by SideHow to Reduce LLM API Costs Without Sacrificing QualityHow to Add LLM Failover to Your ApplicationHow to Switch LLM Providers Without Breaking Your ProductHow to Use Multiple AI Models in One Application