Services focused on the Google Gemini line, covering the Pro, Flash and Flash-Lite tiers, suited to long-context and multimodal workloads.
The site itself puts it this way: AI builds natively multimodal models (Spark, Edge, Flash, Core…
Gemini's edge is long context and multimodality. A million-token context window makes it practical to drop in an entire codebase, or to analyse a long video directly — capabilities the other two families cannot easily match yet.
The key difference between services here is whether the long context is real. Printing a window size in the docs is easy; actually handling a million tokens puts demands on the upstream channel and on billing. The test is straightforward: feed it a long document close to the stated limit, and see whether it is handled completely and whether it is quietly truncated past some length.
Multimodality works the same way. A page may claim image, video and audio understanding, but only real material proves it — video input in particular asks more of the channel, and some services fail silently with a "not supported" response.
A practical concern is how billing is defined. Long-context requests carry a lot of tokens, so if a service re-forwards them and breaks caching, re-sending the same conversation pushes the cost up sharply. For long-document work, prefer services that support context caching.
The picks below are computed live from the current measurements, not fixed conclusions — change the data and the picks change with it. Each states its basis, and you can open the detail page to check it yourself.
The top 1 services by overall score in this category. 0 of them are confirmed to expose a /v1/models endpoint — that figure comes from probing, not from the services' own claims.
| Service | Region | Uptime | Latency | Models | Payment | API |
|---|---|---|---|---|---|---|
|
Reka
reka.ai
|
Global / overseas | 100% | 953 ms | — | — | Unconfirmed |
The questions we see most often about this category. The guidance applies to the category as a whole, not to any single service.
Not always. Some services list Gemini Pro but cap input at a much lower length, returning an error or truncating silently beyond it. Test with a document close to the stated limit, and plant a question inside it that can only be answered by reading to the end.
Split by task complexity. Flash is cheap and fast, a good fit for classification, extraction and format conversion; Pro suits work that needs reasoning and long-context comprehension. In practice, run everything on Flash first and move only the traffic that falls short onto Pro — that is the cheapest arrangement.
Less predictable than image input. Image support is common; video and audio are implemented by only some services. If you depend on them, run a full test with real material first rather than building against a feature list.
The key is making context caching take effect: put the fixed long document at the front of the request and the changing parts at the back. That matches the vendor's own guidance, and it depends on the relay passing the cache fields through. Our detail pages record each service's probe results, which is a reasonable place to start filtering.
This page shows you what exists; the pages below show you who is more stable, faster and cheaper. Read together, they tell you more than either alone.