ParseRail
Paid
Teams needing reliable document AI APIs
Every time you swap providers — OpenAI to Anthropic, Anthropic to DeepSeek — you're touching client code, updating auth, rewriting endpoints. 1endpoint puts a single base URL in front of all of them so the swap is a model ID change, not a refactor.
The gateway accepts OpenAI and Anthropic request shapes natively, so existing client code points at one base URL and keeps working. Prompt caching is baked into the billing model: by message 12 of a conversation, the vendor's published illustration shows costs running at roughly 3.5× less than uncached, because only the new tokens pay full price inside a rolling 30-minute session window. Token-level spend tracking records usage per successful response with no blended platform fee hidden in the rate. The ceiling appears when a session lapses — the window resets, the first request pays full price again, and teams with long-gap workflows lose most of the cache benefit. There is no self-hosted option, so every request leaves your infrastructure.
Bottom line: Pick this for high-message-count chat workloads where cache hit rates are predictable and latency to an external gateway is acceptable — abandon it when your compliance policy requires data to stay on-premises or your sessions are too sporadic to hold a cache window.
Pay per token; 1,000 credits = $1; input starts at $0.0300 per 1M tokens
View full pricing on 1endpoint.dev →
Pricing may have changed since last verified. Check the official site for current plans.
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More options in Model Hosting APIs. Compare pricing, platforms, and features side by side.
Paid
Teams needing reliable document AI APIs
Freemium
High-volume structured decision APIs
Switching LLM providers mid-project normally means touching authentication, endpoint URLs, and sometimes request shapes. 1endpoint is a paid API gateway that presents one base URL accepting OpenAI chat completions, OpenAI responses, and Anthropic messages formats — the model ID in the request is the only thing that changes when the workload changes. The catalog spans flash-class and reasoning-class models from GLM, GPT, DeepSeek, Gemini, Minimax, Kimi, and Opus families, priced per million tokens with input, cached input, and output billed as separate line items.
The differentiating mechanism is prompt caching with a committed rate band on marked models. Because each message in a conversation resends all prior context, the gateway charges full price only for tokens not already cached. The vendor’s published illustration — 12 messages, each adding 10,000 input and 1,000 output tokens — puts the cached cost at roughly $1.06 per 1,000 requests versus $3.70 without cache at GLM 5.3 Flash rates. The cache window runs 30 minutes, restarted by each successful request; a gap beyond that resets the session and the first new request pays full price.
The tool fits teams running high-volume chat or RAG pipelines where sessions are dense and continuous — customer support agents, document chat interfaces, coding assistants with long context. It breaks for workloads where sessions are sparse or asynchronous: the cache window closes, the economics flatten toward standard per-token pricing, and the routing abstraction stops justifying the external hop. There is no self-hosted deployment path, so teams under data-residency or compliance constraints that prohibit external API proxies have no workaround.
Integration is a base URL change to https://1endpoint.dev/api/v1 and an API key swap — POST /chat/completions, POST /responses, and POST /messages all work against the same host. Spend tracking records usage after each successful response at the currently configured rates, with no retroactive adjustment; the blended reference rate shown in the catalog assumes 70% cache hit and output at 25% of input volume, which is a comparison reference, not a billed construct.
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