API bills for AI models turn into a fixed cost you cannot ignore once usage grows. Cheaper Inference is an inference gateway built to bring that spend down without rewriting your code. It buys up the inference capacity that OpenAI, Anthropic, Google, DeepSeek and others have committed to but not used, then resells access to those models at a discount through a single API. It is operated by Keak AI, Inc., a company whose main product is a CRO (conversion rate optimization) tool, and it launched relatively recently, in 2026.
Key Features
- A single OpenAI/Anthropic-compatible API: Migrating is a matter of swapping the base URL in your existing OpenAI-compatible SDK or Anthropic Messages API calls. Request formats stay the same, which makes it practical to drop into a product already in production
- One pool across multiple providers’ discounts: It buys inference commitments that OpenAI, Anthropic, Google, xAI, AWS Bedrock, Azure AI and others reserved but did not use, and offers them at a discount. A single key reaches dozens of models
- A live price catalog and price history: The dashboard shows the current discount for each model, and a price history page lets you trace how rates have moved. You can see which model is cheap right now before deciding where to send a request
- Zero data retention option: On supported routes you can choose not to have request and response bodies retained. Only usage and billing metadata is recorded
- Prompt caching: Where the underlying model supports it, cache control is available — useful for holding costs down when you repeatedly send a long system prompt
- Integration guides for developer tools: The official documentation includes setup steps for Cursor, Claude Code and Codex
Pricing
| Plan | Pricing model | What it covers |
|---|---|---|
| Pay-as-you-go (prepaid) | No monthly fee, pay for what you use | Fund your wallet starting at $5. No routing surcharge on top, and prices never exceed each provider’s direct list rate |
| Enterprise (evaluation program) | Contact sales | A program for validating cost, quality and latency against a known workload. Includes security settings such as zero data retention |
Pricing is current as of September 2026. Check the official site for the latest rates.
There is no fixed monthly plan table; discounts per model move with actual supply and demand. On the top page as of 19 September 2026, discounts of roughly 36% to 70% were displayed, but that is only a snapshot of that moment. Because rates fluctuate, always check the live prices on the official site before adopting it. Enterprise pricing is not published.
Pros & Cons
✅ Pros
- Because the API is compatible, the migration work largely amounts to swapping a base URL and an API key. You can try cutting costs without breaking existing code
- There is no monthly contract or minimum spend, so a $5 deposit is enough for a production-equivalent trial. If it does not pay off, backing out is an easy call
- Discounts across models sit on one screen, which cuts down the effort of hunting for a cheaper model at comparable quality
- Zero data retention and prompt caching are selectable, so it can stay on the table for workloads that touch internal data
⚠️ Cons
- Because this is resold surplus capacity, availability and discount rates per model move with supply and demand. That makes estimates hard, and it fits poorly with projects that need a locked budget
- With no fixed plan table, the monthly total is difficult to project in advance
- As of September 2026 the service is still young, and third-party evidence of its track record is thin
- Keak AI, Inc.’s main business is CRO automation, and public information does not reveal how much weight it will keep putting behind inference resale
- Its GitHub organization has no public repositories, so you cannot verify the implementation in code
Comparison with Similar Services
| Service | Form | Difference from Cheaper Inference |
|---|---|---|
| OpenRouter | The earliest and largest unified API | Passes provider pricing straight through, with a fee on credit purchases. Ahead on model coverage and track record |
| LiteLLM | A self-hosted open-source gateway | No broker margin and no vendor lock-in, but you take on operations and monitoring yourself |
| Router by Ramp | Dynamic routing | Automatically routes each request to the cheapest model to cut cost. Not a fit when you need to pin a specific model |
Cheaper Inference sits at “keep the model, lower the purchase price.” If you want to automate model selection itself, a dynamic router fits better; if you want to hold operations entirely in-house, a self-hosted gateway does.
Who Is It For
- Developers running a product on an OpenAI-compatible API who want to compare purely on cost
- Startups mixing several LLM providers that want to bring down their effective unit cost
- Teams with workloads such as batch jobs that can be shifted in time, and want to run them during cheaper windows using the price history
- Companies that want to validate price, quality and latency against their own workload before committing to a full migration
Summary
Being able to touch API costs with almost no code changes is this service’s strongest point. Because it is designed as a compatible API, reverting if it does not suit you is a light decision too. On the other hand, discounts moving with supply and demand, and the difficulty of reading how long the operator will stay in this business, are worth factoring into the decision. A reasonable place to start is funding $5, running your real workload through it, and checking the discounted unit cost and response quality against your own numbers.