It took me quite a while to come round to OpenRouter. Originally I didn't understand why anyone would put a proxy between them and an LLM, but it actually adds some quite significant value:
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.
Another neat thing is, they publish hourly caching states for ALL model/provider combinations. I did some research on it to come up with a provider tiers list and found a bunch of open-source 3rd party hosts are simply trash tier https://dirac.run/posts/cache-hit-rates-agents
I would recommend tracking this data over time. I work on Cloudflare's KV cache for Kimi K2.6, and while there are periods where our cache rate is low, we are frequently in the 80-90% range. OpenRouter shows us at 87.3% at the time of this post. We observe cache rates change quite a bit from hour to hour.
True for Kimi, but the results I published are average across the models (CF has over 10 models on openrouter). Your current Kimi K2.6 is over 80% but Gemma 4 26B A4B is 0%. https://openrouter.ai/google/gemma-4-26b-a4b-it
This is also the reason providers like Anthropic scored lower because while Opus 4.7 is close to 90%, Opus 4.5 is 45%
Thank you so much for this! I've been working on exactly this problem this week (which OpenRouter providers have the highest cache rate on average) because cache cost is sometimes half your cost: I'd much rather use a provider with more input caching with a more expensive/better LLM. Your results and lists seem more comprehensive than what I've done so far. Very helpful!
Agents push the full conversation history into context every turn
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)
I’m not sure I understand your question. Every interaction you have with a model in a web page does the same thing in the backend. It feeds the whole conversation history, perhaps with a bit of processing, into the model so it can process the next generation. Filling the context window is how these models retain coherence.
LLMs are stateless, to predict next tokens they need the history. When you write your own agents you will be very selective and might trim context and heavily segment different tasks, but generic ones don't do that (at best they spawn subjects to handle smaller tasks)
That said, the KV cache is very much not stateless, so internally inference APIs will be highly incentivized to route requests to instances with as much a shared prefix cached as possible.
Thanks. If I ran it local, presumably I could keep the state cached forever. Can you "reserve" resources from a frontier provider to guarantee your state stays "hot"? (Analogous to reserving a whole VM instead of a slice)
For OpenAI, it seems like you can't prolong the caching duration for money. Duration is longer during off-peak hours for in-memory caching and up to 24 hours for extended prompt caching. https://developers.openai.com/api/docs/guides/prompt-caching
BTW, the openai responses api has a store parameter and a thread id input. Makes it possible to send a thread id and append a new message, ask for completion. So it feels like keeping the conversation going.
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.
I would disagree. Having all the messages locally and sending them with the request means you can switch inference providers or even models mid-conversation. It also means that the provider doesn't store the entire context, which often contains massive parts of proprietary codebases, secrets and PII and instead the agent harness manages all that.
While a simple `continue thread` API field might seem more convenient, the cost is still determined by the input token count and cache rate, so it just abstracts this crucial implementation detail away.
The main friction reduction, for me at least, is the consolidated billing that avoids extra bureaucracy in corporate environments. The API-translation/abstraction tends to cause more problems than it solves.
I’d prefer something that consolidates billing, but still lets me use providers' APIs directly (or via some "raw HTTP" proxy). There are plenty of unified API gateways, but I haven’t seen one that is just billing/auth in front of the native provider APIs.
Good points. The easy experimentation factor is helpful for development, though I would gently encourage everyone to migrate to the 1st party APIs for pricing at scale.
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.
It’s interesting all the focus on opt-out from training. Sometimes I worry there is an intentional focus on that so people don’t think about the other ways the company might be profiting off our data. Like I pay for Anthropic and they don’t train on that but are they selling my “anonymized” usage data in some other way?
From what I recall, these companies don't offer any option to opt out of your session transcript data being used (and sold!) for "regular" adtech targeting purposes.
Anthropic explicitly state that they don't do this, even if you use the free plan and even if you don't opt-out of letting them use your data for training:
That answers for the "sold" part but not for the "used" part.
I.e. nothing about this statement prevents Anthropic from running ads within Claude, as long as they run the ad-placement auctions themselves, and so aren't leaking any of the data they're using to decide which placements are relevant to which users+sessions. (This is the same thing Google does for SERP ad auctions.)
But actually, and perhaps more interestingly, nothing about this statement prevents Anthropic from building a Google AdSense competitor either. Other sites (or mobile apps, etc) could plop in an Anthropic ad iframe; and it'd be Anthropic's knowledge of your interactions with Claude that would drive what ads would show up in that iframe. The embedding site doesn't know what ads the users are seeing, so that's still not "selling users' data to third parties", per se.
> You should expect that any inputs and outputs are going into someone's training database.
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.
> 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.)
The majority of RLHF data doesn't need this. The majority is software development and/or tool calling where the agent gets a signal back as to if it succeeded (eg compilation errors, test errors). It's true that end-of-trajectory signals (eg, did this task do what you wanted) are even more useful but even partial signals are great for RL training.
> 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?
Isn't this a treasure trove for any model distillation effort?
I've wondered this too - exactly how are our inputs and outputs useful as training data? So I asked Gemini. Apparently using negative sentiment in user or llm responses can serve as RLHF, and the human prompts can also serve as useful data for what problems the llms need to be able to solve. There's also that smaller models can train on and improve from data from larger models but that's less relevant when not switching models in context.
> Clearly anyone who can pay should be using paid models with privacy protections
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.
It's free, but not unlimited. Besides rate limits, new sign-ups get 1000 credits (requests), and once those are gone, they're gone for good. Only business accounts might get a couple of free refills.
Did you know that if you put some money into your OpenAI account it expires after a year? I was very annoyed when that happened, no refund no warning it’s just gone as if it was a promo credit.
Openrouter is very nice since it puts a barrier between you and those suppliers that were supposed to be like utilities. I got the feeling that if OpenAI was left alone they would be nice as a telco.
It's not just comparing all the models, it's also comparing all the providers and configurations of those models.
If you're doing any kind of production AI work you'll end up with outages caused by calling a single provider, OpenRouter seamlessly switching between providers is a godsend for uptime.
But even more than that there's meaningful cost+speed differences.
Here's Sonnet 4.6 being served direct, via Amazon and via Google
The way how you manage the caps in OpenRouter is how every metered API provider should do it: keys have limits, and you can change the limits, and you set the limits to refill periodically, and you can create as many keys as you want.
I love their product and use them myself. But where's the value proposition for investors? Unless they get purchased by one of the large cloud providers, they will get pushed out of the market sooner or later.
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.
If you believe there will be lots of LLM providers in the future, then OpenRouter could be a DoorDash play.
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.
not sure that works as well when they don't own their API though; how much software is openrouter-only in a way that's not 5min of deepseek to patch the source for, or 15min of opus to patch the binary instead
Everyone (except Anthropic) seems to be settling on the same API, so nobody "owns it" anymore. I expect there to be practically no software that's OpenRouter-only.
AWS does not provide nearly as many different models as OpenRouter. Perhaps they have an incentive to not do that, move slower as a big company or more legal risks to consider. If AI model outputs becomes commoditized then having one place where you can switch effortlessly from one to the next based on price might just justify OpenRouter. It could become a commodity marketplace/exchange.
functionally they operate as a marketplace for cloud providers. I feel like there is value there, especially as API costs rise and companies explore cost-saving/efficiency. IMO, this is a particularly attractive value prop in the SMB space, where it is common to interoperate between multiple SaaS/software stacks.
They also do a good job working over the little differences between APIs. Tool calling sometimes breaks on major providers, and OR will patch it before the provider does. Libraries like LiteLLM do this too, but OR is faster.
Billing caps are underrated! I don't understand why they aren't present everywhere. As an indie dev there are some services I'm really hesitant on trying by fear of getting an enormous bill for a mistake, this is even more true with vibe coding IMO.
I’m just not sure they have a moat or a long term play? I put $20 in and tried a few models. Then I went right to the model provider to put in $1000 and avoid the middleman tax. Now imagine a big corp spending millions on AI. That’s a lot of middleman tax.
The value of openrouter isn't as a middleman for users of claude, gemini or chatgpt, it's for those looking to find a model that fills the use case at a lower price than the top 3.
Except the latency is significant and not suitable for clients with advanced agent features. The experience between using a frontier model via first party API and the best open weight models via OpenRouter is night and day. Can't get any real work done with it.
The top model / prices are changing all the time though. Lately I've been auditioning 4-5 models before a big ingest and I wouldn't be able to do that easily without OR.
> Long-running tasks like batch mode completions and agent sessions may incur overages beyond your project spend cap.
> 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.
Would you recommend Kagi Ultimate over OpenRouter? I'm already a customer of Kagi and would rather give them my money, but only if I'm not really compromising.
Out of interest, why OpenRouter over a free option like Cloudflare’s AI gateway or another paid option like Vercel’s — any specific benefit to OpenRouter you’ve found, or just first you used that’s good enough?
I didn't know about these options either. I am using Cline: Cloudflare isn't an option but Vercel is. My spending is pretty low overall now that I'm using local models much more but good to know that there are cheaper alternatives to try or at least suggest to others.
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.
Unfortunately the model companies will simply reinject the friction by mandating BYOK (Bring Your Own Key -- i.e. the end user must onboard with each model company individually).
The biggest benefit is that it creates competition among models. If more people use open weight models or models from other providers, it’ll be harder to ban them. Which is what OpenAI and Anthropic will try to accomplish. OpenAI by lobbying the Trump administration for favorable treatment (see Brockman’s MAGA PAC donations), Anthropic by using religious leaders and nonprofits to push “safety” justifications for difficult regulations.
Hi HN! OpenRouter co-founder and COO here. Lots of questions about why we raised!
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!
The Openrouter website says that y'all do not train on the data, but it does not make it clear that the data is not shared with any 3rd parties (other than the LLM provider) who might train on it.
There is the example of Apple and Google providing transport for push notifications, but claiming to delete the content and only preserve the metadata.
What is Openrouter's policy on this? Is the logging of user data an essential part of the business model, or is the primary business model really facilitating a proxy between multiple services and nothing beyond that? If everything is logged, do y'all store it securely so that if one database is stolen (by China for example) then it's not useful on its own?
With the race for AGI and everyone training on each other's outputs, Openrouter is clearly in a position to abuse all of that even though the major providers weaken their output to limit the value of distilling them.
We have two mechanisms whereby we retain data. Both are opt-in and off by default.
One mechanism where you get a discount and we can use the data (in theory this does mean sell it; but our intent is to use it to make efficient dynamic routing solutions. But absolutely we could one day sell it) and another where we retain it for you so you can see it in your logs. We have no rights to this data in any way. This is similar to how any tracing/logging solution works.
Both and opt-in. If you don’t opt in, we don’t retain anything and are a pass through with regards to your prompt data.
All of this is carefully documented and I encourage you to explore and chat with the docs.
What will OpenRouter use the $100m for? You say that it "makes the company extremely durable" and is "good validation to employees", but I'd imagine that there are more interesting things to do with 100 million dollars.
Everyone wants a conspiracy, but what I originally posted is in fact the boring truth. Having a bunch of cash in the bank makes for a durable business!
> 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!
That's a nice narrative but I suspect you're not touching upon the investor pressure side of things. Your earlier investors would be upon you to show a multiple in valuation beyond what the balance sheets can show. The only way to do that is to raise more money.
The problem with this is that you're now beholden to another set of investors who will also expect a multiple on their investment which makes increasing valuation your primary objective, even to the detriment of the business. With a margin business you could sustain for a long time even when the market stagnates, but you've lost that option when you first took money from someone. It's an all or nothing play now.
I’m interested what you believe the intent of your message to be. You’re talking to a COO that just raised money as if you’re mentoring someone about to approach VCs for the first time. Hugely patronizing attitudes often just get a pass here on HN, but what is your purpose for using one here?
I think you misread my comment, I might've been lazy in constructing it. I don't mean to mentor anyone, rather I'm putting out my read of the situation so there's a common ground over which to discuss.
For me, raising $100m when it's not needed doesn't add up. Nobody lends money with the idea to "keep it, just in case". There are always commitments and expectations and obligations to meet those expectations. So when they said they didn't really need to raise, while also not talking about investor expectations, feels there's more to the situation than is being let on.
By default (and in most cases) investors and operators are aligned. When we diligence our investors, we call companies they worked with where things didn’t go well, and speak to those founders. Understanding how investors operate when it’s not all up-and-to-the-right is important when picking partners!
Heya! First off, I love your product. consolidated billing/auth solves a big pain-point, so thank you.
Less about the funding and more about the long game: where do you see OpenRouter in 3-5 years, and which product bets are you most excited about right now? Do you guys think with this new raise you'll branch out into other adjacent verticals?
Our general theory of the case is that, in the not so distant future, inference will be the second largest opex line item for most companies (behind headcount) and that sourcing, measuring, and governing those tokens is a massive horizontal opportunity.
We will inevitably expand into adjacencies because we like building things and experimenting and we have a lot of people with great taste who are likely to ship cool things that customers want to use!
Would it be possible to get "raw" access to the provider APIs, but still keep the consolidated billing? The unified API is great when it works, but it often causes hassle with more exotic use cases and new API features.
+1 this. Example: Using Mistral TTS voice cloning appears to be not possible via the "providers" pass-through object in the OpenRouter API because some parameters are always forwarded which conflict with the provider's parameters.
Interesting. Will look into it! We are releasing pass through API params soon which might hit the bid, but is a bit different than what you are describing.
API param passthrough will probably help with many of the cases. Things like sampling params and constrained decoding and returning logits tend to be very finicky with the translated params. But the return value translation also makes debugging these harder.
While I'm at it, another annoyance is that OpenRouter doesn't seem to have a very good API playground. The chat does work, but the params exposed there are quite limited and it's not clear how the GUI fields map to API params. I now have resorted to exporting the chat and figure out the params from the export JSON. Just having an option to get a curl command for the chat call would help a lot, and shouldn't be hard to implement.
Edit: I think the ideal implementation for the direct API access would be that I could generate API keys for the provider at OpenRouter that I would give in the provider API calls, but that would get billed through OpenRouter. Second best would probably be a raw HTTP proxy/tunnel that injects OpenRouter's own keys (or however it is that you call the providers). I don't really know though how you call the providers and what kind of new provider integrations these would require.
Refund policies are clearly documented in our terms. We actually DO offer refunds within 24hrs of credit purchase, which is significantly more flexible than most companies that operate in a similar way. And we try to use good judgement when there are extenuating circumstances.
The biggest missing feature for me is the differentiation on zero data retention providers and if a model works for the rules I defined. Right now there’s no way to hide the providers who don’t work for the zdr rules
What differentiation are looking for? We have good documentation of every provider and what their data retention stance is, and you can figure allow/blocklists for all providers.
Check out the Guardrails section under settings and tell me what’s missing!
Thank you for Openrouter, used it briefly. Tested the product a year ago or so, and wasn't able to get structured output from google's gemini model via openrouter.
As someone who uses OpenRouter extensively (and wrote an unintentional adjacent PR piece a few days ago: https://news.ycombinator.com/item?id=48317294 ), it's definitely the best way to try out new models without fiddling with each providers distinct APIs which is becoming a recurring concern as of late.
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.
There is a lot of dumb token spend right now - tokenmaxing and such. Economic cost of token is not being evaluated carefully because there is fomo and no one wants to be left behind. But folks are waking up to it, and dumb token spending is not sustainable and will revert.
IDK, but that sounds like something that would be better implemented with an open-source library to which providers supply support patches. Why do I need a company to act as a proxy and not just run a relatively simple shim layer on my machine?
I'm just a stupid systems programmer working in the bowels of AI and I understand there is a lot of seemingly pointless software which exists solely to provide a slight boost to convenience in exchange for money. Is OpenRouter just that? Do they actually host models themselves or centralize billing amongst various providers?
A library with a bunch of different providers doesn’t solve the payment/billing problem (which is one of the main openrouter benefits). IMO being able to buy credits and not have them locked to one provider is worth the 5% to me.
>> it's definitely the best way to try out new models without fiddling with each providers distinct APIs which is becoming a recurring concern as of late
Cursor only supports a single model (Kimi K2.5) not made by the Big 4 labs (OpenAI, Anthropic, Google, xAI). Cursor is actually extremely bad at wide model support.
I use Cursor with OpenRouter for some projects and it's great. Most of the time I just use Auto and let Cursor use its model or choose. If I run out of quota, or I'm not getting what I want, I switch off Auto and use OpenRouter to pick Opus, Codex, or whoever(all are available). Can continue the same context if you want, type "please continue" in the agent prompt, and on you go.
Cursor has limits even when using your own key. I was even cut off using a local model. I guess they use some sort of harness that requires non-local resources? I'm not sure I've actually tried to use Cursor in a fully-offline scenario yet. Cline works well enough and doesn't require any sign-up.
I think that OpenRouter will continue to be very popular while there lots of experimentation in the LLM space, and while the "current favorite" model continues to change between various frontier labs.
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.
Is the Open in OpenRouter the same as in Open AI? I couldn’t find any repository or hosted code. Thought it'd be a open source, self hostable tool with a cloud offering but seems its just the latter?
I assumed they were open source but now that I checked they are not, they say "Open" because they route to third-party open models. Yikes. Another VC crap layer?
Today your statement is a little too ambitious but I agree with the overall point that the inherent effort based moat in SaaS is mostly gone and now it is really about personalizing your own.
The most common counter-argument that I've seen here is " Yes, but no organization wants to manage all of their different operational tools. They would rather just outsource that responsibility to third-party entities".
I'm not sure I fully agree with that counter. Because agents can be viewed as third party entities in some sense. If not today then maybe soon.
One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish that other providers would make possible/easier.
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.
One thing I haven't seen mentioned here yet and really like about OpenRouter is their openrouter "meta" model, that automatically routes the prompt to an appropriately capable model. Saves me a ton of money on not routing everything through Opus, but not giving me bad results when I ask something more complex, which gets autorouted to Opus.
Assuming that's token cost upstream, and given the multiplication factor in tokens processed per query, that seems like maybe a few thousand requests per second at most? It's impressive but for a 50 person startup team expending millions per month, that seems about on par.
Would it be as impressive if the context were an email provider accepting thousands of message per second, or even one accepting thousands of messages per second and submitting them upstream for spam detection? The token count might even be higher in that case, but rightly or wrongly I think it would get a yawn on HN.
It says more about how far the industry has come these days in terms of scale on the one hand, but also on the other hand the huge blowup in data and processing for nominally simple requests. Nonetheless I'm sure the team is exceptionally skilled and it's certainly a laudable accomplishment.
Dealing with a lot of traffic for a small team isn't hard in itself. If it is easy to parallelise you just need to horizontally scale. And most concerns can be added as sidecars or middleware. Rate limits, auth, etc. Basically this is a kubernetes cluster. For a 3 person startup hard. For 50 pretty managable.
They are because they can, because it serves as social proof, which convinces their customers that they are doing something of deeper value. Then in reality they will use it to develop channels preparing to use their customers (and the data customers trust them with) as the product in the future.
That signals the reverse that they might jack up prices at any time for their 10x returns for the investors. How does that instil any confidence at all?
I’m still pretty skeptical about OpenRouter. I have a client implemented for them so I can use them with my harnesses, but at the same time that client was generated and tested in an hour or so just like all of the other llm provider clients that I have. Using these services interchangeably by just swapping out clients has so far been working well for me. I think when it comes down to it, the only real inconvenience that they’re solving is where I put my credit card number. Is there something key that I’m missing about this service (besides it being a nexus of attention) that warrants this kind of investment? Or is this truly the bar for starting a successful AI company :P
I was sort of hoping that they were bootstrapped or at least non-VC funded. I'm wary of them introducing consumer-unfriendly revenue-generating schemes.
Hm. Would be interesting to see the finance spreadsheets for this. Typically the B-round guys are looking for something approaching a 10x return. Can anyone justify OpenRouter being worth $1.1Bn? That seems really high for a “management”/man-in-the-middle play. But sure, AI and all. But I’m old enough to remember when every dot-com was a billion dollar valuation, too.
Well yeah if they route most of the worlds tokens easily. What if we get to a point where the 5% is paid by the supplier and they take over more of the infra /routing side that they do. Lots of ways it could be a 10B company.
But is that likely, particularly as the market matures? That seems unlikely to me. We had some of the same sorts of management middleman tools and organizations ideas 15 years or so ago in the cloud computing world and all that pretty much went away.
Congrats to the OpenRouter team for securing this round of funding.
The 5% surcharge for their pricing model may not be palatable to enterprises. In fact, the OpenRouter team could be a pivotal part of the enterprise GenAI stack if they can allow configurable, pluggable endpoints for routing directly to enterprise vetted endpoints to 1P/3P LLM APIs. A couple of large companies I’ve worked so far kinda have this system in place, albeit the dev and maintenance cost and of setting up such an “LLM gateway” could be significantly reduced with OpenRouter. I feel that this is largely an ignored, forgotten part of operating GenAI apps at scale.
> The 5% surcharge for their pricing model may not be palatable to enterprises
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.
OpenRouter’s biggest value to me is reducing switching costs between models. The markup matters at scale, but for exploration and early-stage development, the convenience is hard to beat.
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?
Yes. Happy for the team but I do not like that this likely means for the future growth expectations as a customer. Hint: probably higher costs and being squeezed more.
An amazing service. I use its 20+ free LLM options to allow completely free usage of LibreOffice AI extension with no signup https://librethinker.com .
I'm banned from using the free options. At some point they flagged my account as having engaged in model training against their ToS. This despite my account using around £15 worth of tokens over several months, nearly entirely through BYOK providers.
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).
My usage of OpenRouter was limited to casual throwaway experiments with coding agents and quick, surface-level exploration of new and unfamiliar models in the chat interface.
My comment is just an expression of a festering grudge over the unannounced, unexplained sanction on my account and the lack of transparency and feedback from the non-existent support team. There's no OpenRouter shaped hole in my personal workflow, fortunately.
If you want to avoid bans, Venice is another good option since their focus is uncensored and privacy. They run models themselves alongside offering OpenRouter-style routing for frontier and niche models - but at least they fully anonymize the user and never ban.
I still don't get the value proposition: You rarely have to use all the models, you will likely end up with a few for your workflow but there is a way to use them/try all if you wanted to, neato.
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.
agreed, unless you need to use all models i'm sitting here wondering why orgs would want to introduce third party risk into their pipelines for marginal cost and time savings
OpenRouter is our primary provider for evaluation data, and we've been really happy with them!
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)
What's the business model? Their core functionality, while useful, seems like something that will just be an open-source package. I assume there will be some Saas layer on top of it?
Collect and sell data would be my guess. Without ZDR by default they are in a position to collect a crazy amount of data that I’m sure various buyers would be interested in (not just the big labs).
I think subscriptions are not going to last for serious users. Great to use them while we can, but AI does not fit the “power user subsidizes free/cheap users” model, nor the “support tens of thousands of customers from a small number of cheap servers” model. Everyone is a power user, and everything is computationally expensive.
Chatbot windows are a waste of time compared to API tools when trying to make stuff.
Subscribing to a vendor locks you in to sudden price swings that the big 3 are happy to do. The market needs lubrication for competition and provider routers offer that.
> ... with participation from NVentures (NVIDIA's venture capital arm), ServiceNow Ventures, MongoDB Ventures, Snowflake Ventures, Databricks Ventures ...
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.
The real moat will be the user base they've built during that time. I could copy every feature of their website within a few weeks, but I couldn't copy that.
Why does a company with a seemingly health business model that is already churning profits and doesnt require large CapEx, taking losses to capture users, need to be raising this kind of capital?
i wonder if it's partially because it's not a unique business model and subject to yet another VC-subsidized race to the bottom on things like token prices
In what way? They're just an API customer like any other and charge a bit more on top. Providers would have to carve out their usage terms to not allow resell, which does nothing besides lose customers to competitors. If they all did that then you would tap on the FTC's shoulder and suggest they do their job.
One well known problem with OpenRouter is routing to poor quality model providers who quant the models.
So you think for example you're using Kimi k2.6....but behind the scenes, it's the 4b or 8b quantized versions.
So for open source models, I've started using the providers own service. In the case of Kimi, I don't trust any provider other than moonshot not to quant the model. So far this seems to be getting better results.
If I see a provider not specifiying if they quant or not, I assume that they do.
I'll still use OpenRouter to try new models out, but not for any real work.
I like OpenRouter - lets me test out new model quickly and easily. I would still need a good functioning mobile application for it.
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".
Venice (uncensored privacy AI API and app co) took a year to expand their self-hosted model selection to routing hundreds of other models. It's harder than it looks to get customers. But they did grow to 3M users and >$50M ARR as of a few weeks ago. So go for it if you've found an easy way to do it.
I'm reading the website and nothing about this addresses the compute running the models. If that's going to a third party (just like openrouter is), then there are no guarantees, other than words on paper.
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.
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