First off: We remain founder-led and founder-controlled, and intend on being here for a long time, creating awesome products for builders all over the world. We are basically a bunch of tinkerers who like building things, and try to make stuff that we would like, when building with AI.
Since this is about the raise though, happy to share perspective on it.
We believe that strong companies should have a strong balance sheets. We touch large volumes of spend, and have large spend commits across the ecosystem; having the cash to withstand what may come is a responsible buy-down of risk, and makes the company extremely durable.
It also tells our larger customers and provider partners that we will be able to continue to serve them (and pay our bills) for a long time to come. We don't need venture dollars to continue scaling (indeed the business is healthy) but you know when you don't want to raise $100m? When you really need it!
This is also good validation to employees (current and future) that the value we are creating together is real. We also take seriously our obligation to make a return for anyone who invests; we aren't valuationmaxxing and have the privilege of getting to pick who we work with. I don't think that gets a lot of airtime in the overall start-up world, but I think it's important!
Happy to answer questions and THANK YOU to everyone here who uses OpenRouter, and to everyone who has feedback for how we can improve!
That said, I don't understand the people who use something a full agentic backbone with expensive models like Claude Opus with OpenRouter because that 5% surcharge is meaningful at that level of cost instead of going with the source API providers. But people are clearly doing it, and it's pure revenue.
Why not... Cursor?
OpenCode is much better at it.
Infrastructure? For proxying requests more infrastructure? You could just pay Cloudflare.
More engineers? But you yourself are the stret seller for the same snake oil that engineers aren't anymore necessary
So what that 100 million dollars are for?
So many use cases, like sharing AI/assisted features externally, with the ability to use those features but also limit the fallout if its shared / used for other purposes, without jumping through more fallible hoops like safeguards etc.
its just a proxy
After things begin to settle down, we'll probably see a consolidation of both frontier and open-source models - and then OpenRouter will become less useful, because that 5% overhead is well worth it when you want to try 20 models from 10 labs, but harder to stomach when you only need 5 models from 2 providers, and each of those providers has its own API knobs that you can tune to make things even cheaper.
DAMN!!
That's 41+ million tokens every second. That scale is crazy for such a small team of 48-50 people overall.
Enterprises appear to be paying the API rates which are 10x (1000%) what are available to individuals, so I would not be confident they are sensitive to a 5% price change.
That said, the attraction of OpenRouter to enterprise customers should be that they save you >5% on average for a product <5% worse.
I’m a user and I like the routing layer and not having to change things up too much, but I’m not sure why a solid business model for this product would require this much money at this kind of valuation unless they’re trying to buy data center capacity to self-host models eventually?
Also one scary issue I had with OpenRouter in the early days, I think I saw somebody else's context and there were weird Chinese characters, haven't touched it since.
I'm sure they're experiencing growing pains, but a larger model selection (and faster releases for open weights models), would keep us from using other providers. For example, it took much longer than it should have to get Qwen 3.6 ~30B class models released (almost 2 weeks if I recall)
The handful of times I did try a free model is when I used their chat interface to quickly compare a few open weight models with a single prompt. That's the only usage I can think which could have triggered the block on my account. Even still, what's the point in have the simultaneous chat feature if using it veers so quickly into a ToS violation.
Their support is beyond useless in helping understand the situation. I don't think I managed to speak to anyone other than Tony Bot (or whatever it was named).
Edit:
Total usage over 1 year:
Claude Sonnet 4.6 $8.80
Gemini 3.1 Pro Preview $6.71
Claude Opus 4 $6.19
Claude Opus 4.1 $7.49
Gemini 2.5 Pro $10.06
Claude Sonnet 4.5 $12.74
GPT-5 Codex $2.56
Grok 4 $4.39
Gemini 2.5 Flash Image Preview (Nano Banana) $1.88
GPT-5 $7.30
Others $7.99
Are tech companies FOMOing so hard that they're now all running AI venture arms themselves instead of you know, developing their own products? Except for NVIDIA who needs to keep pumping the bubble I didn't expect the others.
Well, at least for them, investing into AI is actually developing their own product. The push to replace "Actually Indians" [1] with LLMs is huge because large Western companies want to save even the pittances they're paying Indian body shops.
[1] for those OOTL: https://www.reddit.com/r/ProgrammerHumor/comments/1l3rpow/ac...
I think they should go in this direction: they should make their own Model Agnostic versions of whatever functionalities other AI companies are making. Examples
1. personal chat app
2. the chat app working with their own implementation of memory
3. coding harnesses that are model agnostic
When I think of OpenRouter, I should think of "model agnostic LLM tools".
1. By far the lowest friction way to support and try out all the models.
2. They offer billing caps! Most model providers still don't do this [EDIT: maybe they do, see reply comment], but if you're going to run anything in public it's very useful to have hard limits so it doesn't cost you $1m overnight because someone started abusing it.
3. Their rankings are one of the more interesting signals for which models are popular, despite their flaws (most OpenAI and Anthropic users don't go via OpenRouter, it's currently not possible to tell the difference between many users switching v.s. one "whale" changing their preferred model)
Given how API costs are becoming meaningful for a lot of companies now, having a provider like OpenRouter to help measure your spend and easily experiment with and switch providers feels like a valuable service.
This is also the reason providers like Anthropic scored lower because while Opus 4.7 is close to 90%, Opus 4.5 is 45%
Why?
Maybe this is a dumb question, but why wouldn't an agent "keep the conversation going", like I do when interacting with an LLM through a web page? (I understand how it's impractical for long-running tasks where the agent has to wait days for the next input, but assume that's not the majority of use cases)
Technically it does retrieve the entire history and reevaulate it since the LLM is stateless. Just more ergonomic for the developer.
And prompt caching helps cut the costs down when a conversation drags on.
OpenRouter is also a good place to find free LLM access with a catch: You should expect that any inputs and outputs are going into someone's training database. Clearly anyone who can pay should be using paid models with privacy protections, but the free models have been great for learning and experimenting. Especially for younger people learning API programming and LLMs who may not have access to a credit card or funds.
True enough, in theory; but what exactly are you imagining would be a useful-enough signal in the OpenRouter request+response stream, that any company would want their data as training material?
Even a single OpenRouter-API-key-identified subscriber's traffic, may consist of an mixture of traffic from multiple different sessions, under potentially multiple different end-users. (Where, if the subscriber is doing security correctly, then their OpenRouter key lives on a gateway rather than in a frontend app; and so the only IP address / UA / etc OpenRouter sees is that of the gateway itself.)
And the traffic stream may also invoke multiple models, and provide multiple different system prompts for those models; which, while marked in the traffic (i.e. conveyed as part of each request), makes the resulting data much less useful in aggregate, than if it were all training data for one model with one system prompt.
Plus, there are no RLHF signals in OpenRouter data. Even if OpenRouter wanted to build a general model-neutral framework for collecting RLHF-type data, it can't force subscriber apps to do the UI-level stuff necessary to collect it (i.e. the things ChatGPT/Claude do, with "thumbs-down" buttons, A/B tested responses, etc.) Analysis would have to rely on pure transcript-level user sentiment extraction.
Clearly, anyone who needs privacy should be using models with privacy protections. Some people build open source and the models will get the code anyway.
https://news.ycombinator.com/item?id=48319827
What's the value proposition for the typical AWS startup to go with openrouter, if Amazon offers similar rates with direct integration into all their other offerings?
The only reason OpenRouter can exist at the moment is because we are in the wild-west phase of this technology, and lots of people and companies are exploring. In 5 years they will have to have transformed their business fundamentally, or go the way of the dinosaurs.
Established restaurants didn't need DoorDash because they were already on everyone's speed dial. But new or small restaurants couldn't afford to advertise or maintain a team of delivery people. DoorDash created a two-sided marketplace that made it a lot easier for new entrants to bootstrap. Today even the established restaurants have to pay them their tithe because hungry people have learned to start with the DoorDash app. A bit of a prisoner's dilemma.
If OpenRouter plays its cards right and gets very lucky, a large number of people will configure their hungry LLM clients to start with OpenRouter, and then LLM providers will have to join the marketplace or else miss out on all those customers.
Everything has a cost of some sort. It's just who you're going to pay and what the currency is.
What if Fireworks stops offering your preferred model?
Anthropic: https://support.claude.com/en/articles/8977456-how-do-i-pay-... - you can pre-pay and get a hard cutoff.
OpenAI: https://community.openai.com/t/how-to-set-billing-limits-and... - last time I looked OpenAI had a soft but not hard limit, I guess they fixed that last year.
I remember bugging them both about this last year, I need to update my mental model!
Deepseek has a prepaid model. (Pretty impressive, what fits into 10 Dollar)
> Billing data processing times can be delayed in AI Studio, up to around 10 minutes. You may experience overages beyond your project cap if billing data hasn't processed before more charges are accrued.
https://ai.google.dev/gemini-api/docs/billing#project-spend-...
That's a soft cap, not a hard cap
Check out Kagi Ultimate.
Looks like Vercel even have their own leaderboard: https://vercel.com/ai-gateway/leaderboards/models
Surprising that they have Opus 4.8 and 4.6 listed on the leaderboard but not Opus 4.7.
Other features I've just noticed: - configurable prompt injection protection using OWASP regex (https://cheatsheetseries.owasp.org/cheatsheets/LLM_Prompt_In...) - configurable PIM protection for outbound prompts - input/output logging - "JSON healing" to auto-correct minor hallucinations
Lots of other stuff too. The business model seems pretty simple and the value-add features don't look particularly expensive or difficult to copy.
They don't list themselves on https://openrouter.ai/providers
https://openrouter.ai/openrouter/owl-alpha
coffee farmers -> middle man -> you