LU Cloud and Featherless
Compare the billing structure and limits that matter to your workflow. This is not a performance benchmark or a price-per-token ranking. Different credit units are not interchangeable.
Checked . Plans can change. Follow the sources and recheck before purchasing.
| Question | Featherless | LU Cloud |
|---|---|---|
| Plan structure | Feather Chat is USD 25 per month, with four concurrent units and context up to 32K. The Developer offering starts at USD 50 per month and uses credits.: Featherless plans | Credit packs start at EUR 15 for 450,000 credits without a subscription. Context and model capabilities are listed individually on the LU pricing page; full native context is not promised.: LU pricing and published limits |
| Capacity accounting | Requests reserve model-dependent units while running. A four-unit budget can support one request costing four units, not necessarily four requests. Requests exceeding the unit budget receive HTTP 429.: Featherless concurrency documentation | The Flash app-session path on an active paid plan admits one request at a time per account. It is a request limit, not a model-size unit budget. Paid routes have separately published request limits.: LU pricing and published limits |
| Usage model | Chat plans describe unlimited monthly requests subject to their concurrent-unit budget. Developer plans deduct model usage from a monthly credit balance.: Featherless plan types | Flash app sessions have a 500,000 combined input/output token allowance per account per day. Reservations that cannot fit follow the visible credit path. API keys use credits, including for Flash models.: LU pricing and published limits |
Check your actual workflow before choosing
Compare the models and input modes you need, request size, concurrency and billing period. A large advertised context or credit balance alone does not establish how much useful work a service will perform for you.
Read LU's cloud capabilities and restrictions before buying. Hosted requests leave your machine, and image and video generation have content restrictions. Local inference depends on your hardware and backend.