[tyleo]

I’m suspicious of some quotes here, “80% of startups using Chinese models,” doesn’t seem quite right to me. I just interviewed at several startups and they were all using the US models. Maybe they have some minor use of Chinese models but the bread-and-butter of most of these businesses model use is the Claude and Codex subscriptions.

[apparent]

The full quote:

> When entrepreneurs walk into the offices of Andreessen Horowitz (a16z), a big American venture-capital firm, the odds these days are that their startups are using AI models made in China. “I’d say 80% chance [they are] using a Chinese open-source model,” says Martin Casado, a partner at a16z.

This is very different from what the author portrays. It may be the case that many pre-funded startups are using Chinese open-source models (somewhere in their workflow). But what percent of startups that survive more than a year (either with funding or revenue) are still doing this?

I imagine their pitch is: "look at how well we're doing using open source Chinese models! We'll do even better once we raise money to be able to afford frontier models!"

The way the author presents this quote makes me think he had a preferred narrative and found quotes to back it up. Or he's just a very uncareful reader.

[awllau]

Casado says he was misquoted and walked this back: https://x.com/martin_casado/status/1990462245541982546

"Well, not quite. I'd say 20-30% use open source. Of those I'd say 80% use Chinese based models. So closer to 16-24%."

Reads pretty differently.

[kbar13]

yeah and the gap between "use open source" and "use open source as their primary model" is probably p large

[zmmmmm]

yes... I think for startups there's a strong desire to demonstrate technical independence - there's a strong smell with looking like a wrapper on Anthropic or OpenAI. With an open model you can weave a story where you are exercising differentiating knowhow by deploying or tuning models yourself.

[JamesBarney]

This should really be the #1 comment on this post.

[apparent]

Wow, that kind of undermines the entire premise of the piece. It also makes much more sense. Thanks for digging that up!

[JimsonYang]

Misquote? Or selective hearing for the story headline? Thats literally a 4x difference there

[kamranjon]

I don't really think the author is misrepresenting the quote in any way, it just seems like many people are reading it as a hard statistic instead of a reference to a properly attributed quote.

Just anecdotally though, my company is not a startup, well established and well known and has already started investigating, purely for dev purposes (not product), using Chinese models - this was spurred by costs rising much faster than expected.

So while I agree that I don't think it's anywhere near the 80% level across the board - I wouldn't be surprised if it starts moving that way.

[mrandish]

There may be confusion between 'product tech' and 'development tooling'. It's entirely plausible most of the startups that are A: building AI tech, B: early stage, and C: raising from top Sand Hill Road VCs, are currently prototyping their product tech concepts starting from open weight models.

A VC partner meeting with early-stage founders is focused on the viability, uniqueness and defensibility of the IP tech stack not what tooling the coders are using. The developers could be using Claude or GPT 5.6 to develop a tech stack based on open weight models.

[131012]

Could it be that the startups that embed LLMs in a product will prefer Openweights for a more stable economic model, while SWE who use LLMs as a tool prefer SOTA to produce code?

[apparent]

Found the narrative, it was right there at the bottom. Now I remember reading some of his other stuff and it's very much in the same vein.

> I care about having open technology that can be run in the public interest, aligned with the public’s values. Threads like public AI, federated services, and open research have traction but need backing. Getting there in the US needs more nuanced strategy and support than we’re seeing today.

[whywhywhywhy]

This quote sounds like it’s about companies building products on AI to serve a tweaked or harnessed version of that to others not the developers in those companies model of choice for coding.

[munk-a]

It's also important to note that several PE firms have signed contracts with model trainers to specifically use their model in their owned companies. I know Anthropic signed a deal worth hundreds of millions to acquire users just a few months ago.

[soerxpso]

There's probably some selection bias in that stat, too. Based purely on vibes, I wouldn't be surprised if startups pitching to a16z are using open Chinese models slightly more often than startups pitching to other VCs.

[karagenit]

Yep, and following that with

> and Chinese models are poised to take the lead.

makes it sound like the second part is a continuation of the first quote from the same source, but actually the second link is just some random person’s substack post from almost a year ago.

[Aurornis]

It’s a sneaky statistic. You could say that 100% of the startups I worked at used Windows laptops because at least one person had a Windows computer somewhere.

If you saw the engineers you’d see 80% Macs and 20% Linux laptops.

The statistic would technically be true.

I use Chinese open weight models a lot, but they’re not what I reach for when I’m doing important coding work.

[jvanderbot]

I _evaluate_ open weight models all the time. Does this mean I _use_ them? That's a very suspicious statistic.

[philipkglass]

I don't use any open-weights models for coding, but I use them heavily for document categorization and extraction. At millions-of-documents scale even the smallest models from OpenAI or Google cost more than running a small model on my own hardware, and for a lot of tasks I don't need the extra intelligence of proprietary models.

[comrade1234]

We're using deepseek with the idea that we would switch to something better when more of our customers are using the ai features but it ends up deepseek is awesome for what we're doing and so we probably won't switch because it's so much cheaper.

The ai libraries we use let us switch models with just a configuration change.

[x313]

Similar story here. DS models are absurdly good value for mid-end tasks. I've found DSv4 Flash to be ~10% the cost of GPT-5.4-mini/Claude Haiku at similar performance.

We used to pay OpenAI >1m$/month for fraud classification, NER, etc. Sadly the US companies no longer care about non-coding-agent uses.

I imagine uptake will continue to increase as the corporate infra improves. Right now it's still bad - for example, AWS Bedrock is awful, models are months late and implemented with basic errors. Google Vertex is even worse. Finding a decent provider is the hardest part.

[comrade1234]

Yeah we don't use it for coding either. Basically text analysis within specific constraints. It works beyond my expectations.

[brandon272]

Where is your DeepSeek model hosted?

[comrade1234]

Deepseek directly but we can switch to openrouter and a USA host at any time. Again it's just a configuration value - no code changes.

[satvikpendem]

It depends whether it's talking about using models in the product versus for development. For example I have a few apps that use open weight models, whether on-device or via API if Internet is available, but for development I use Claude, Codex, Cursor for Grok etc.

[moduspol]

Our small team (~6 devs) is still using Claude Code because we're still on the cost-per-seat-month plan. If we were being pressed to pay per token, we'd be re-evaluating for sure.

[speu]

Cursor may make up the difference. A ton of companies use Cursor and Cursor's UI and billing model pushes their in-house "Composer 2.5" model pretty heavily - which is a modded Kimi K2.5 model under the hood. Anyone using Cursor is likely using Chinese models at least some of the time.

[alightsoul]

I believe this depends on country. I would believe, US startups trust US tools more. In other countries which see china in a positive light https://www.pewresearch.org/global/2026/07/15/people-in-many... I would expect them to use Chinese models due to their lower cost.

[abe94]

Its a bit more complicated than that quote implies

At posthog we see if a customer is using an llm, they use more than 1 model. The typical pattern is frontier models for a small percentage of 'harder' tasks and then one of these chinese models for more standardized procedures. As you get better at standardizing procedures you are able to use the chinese models for more and more work so token usage goes up, but the $ spend on top models has still been growing

[datakan]

I can believe it with startups as they are trying to keep costs down. Established Enterprise however, is a different story and is where the money is usually. If those startups become successful the story may change, but most of them will fail.

[fidotron]

Yeah. People should absolutely be _trying_ the Chinese models, and experimenting with running things locally, but the noise in development is genuinely all Claude and Codex.

I put my foot in the mobile comparison the other day, and will again. If you were to go back and be a mobile dev in 2010 by all means specialize on one platform, but play with both as a professional interest to stay realistic. Here it's important people have access to US/Chinese/Other, open/closed, local/cloud and that this remains. Don't become a blind Claude guy or a open weights fanatic: that way lies disappointment.

[wordpad]

If startups includes openclaw users then I could see this being true.

Deepseek is barely behind frontier models while 10x cheaper and 99% discount for cache.

[icase]

people still use clawdbot?

[applicative]

Dunno I put to deep seek the question what I’d need in hardware to get full service k3 with lower latency in western pa (I was making like it was a business proposition.) It says several million dollars at minimum.

[JSR_FDED]

Unlike iOS/Android choice which has broad personal ecosystem implications, changing IP address to another LLM provider is effortless.

[pmontra]

Frankly I don't see much difference between Claude and DeepSeek except in the price. I use the Pro plan to work for a customer of mine and I topped up $2 on DeepSeek in late May for personal use. I worked on 3 projects and I still have $0.72 left. The Chinese companies will win on price, not openness.

[01100011]

If if it were true, who cares? Most startups fail. Most are terrible ideas and/or terribly executed. I fail to see why it's a useful metric.

[idiotsecant]

Is your point that startups fail so we should disregard the central thesis that locked down AI will eventually lost to open models?

[parineum]

Not op but that makes perfect sense to me.

"People with mostly bad ideas/execution use Chinese models." Is the point being made.

If you slice it to some measure of success, is the statement "Successful start-ups/companies use Chinese models." still true?

[airstrike]

Hmm if you assume the 80% is uniformly distributed between successful and unsuccessful startups/companies, which by default you should, then yeah, your proposed statement is true.

Data would be needed to argue the 80% skews unsuccessful

[verdverm]

How does this comparison sound if we use cloud provider?

The Ai is writing code, not executing a startup. The code was never the hard part of startups

[parineum]

Deciding to use open models over closed models is a business decision.

[pmontra]

Using the cheaper model is also a business decision. We don't know why they are using the Chinese models: openness or money or both or a third one?

[verdverm]

The point is that for many tasks today, and likely all tasks before long, that the open vs closed will not be a differentiator. There are many open models much better than gemini, yet people still use gemini.

It's like picking AWS vs GCP. Yes it is a business decision, but one that will not likely affect the outcome of the business.

[throw10920]

I don't see that anywhere in the parent's comment. Where did you get all that?

[vel0city]

They probably use Claude and Codex for their actual development, but for the products they actually build and deliver to customers I imagine a lot use open-weight models.

If you're putting a lot of your money and time into a business, do you really want it built on a service only hosted by one company that will turn it off eventually and you have no recourse?

If you build something against an open model you can take that and run it anywhere. If your favorite model provider stops hosting it, you can go elsewhere, you can go rent GPU instances, you can even shell out and buy hardware to run it yourself if you've got the capital and it makes economic sense. Change some API keys, update a URL in your config, and you move on.

If the government decides that proprietary model is too good and so it gets shut off, what do you do? If a proprietary provider decides it's not worth it for them to continue hosting that model, what do you do? If that provider silently updates the proprietary model and it makes your app broken, what do you do?

[lousken]

It depends, I guess if they still dont care about losing money or they already had subscriptions then they keep using them, likely either openai or anthropic. If they noticed the bill going up, like with github copilot, they are looking at the alternatives.

[davidpapermill]

We use US models for everything in practice, but we are looking at open-source models right now. So it may just be a turn of phrase hiding the reality. I can't imagine anywhere near 80% are relying on open-source as their primary models.

[paul7986]

I'm using a ten dollar a month US model to vibe code startup ideas. All my previous startup ideas i had to hire a graphic designer and back-ender or two to help. I use to be a web design front end enigeer since 2009 yet those skills are dumb now, so now Im a vibe coder.

The model I use to vibe code with I am just going back and forth with. Since Im building it as I go using an agent doesn't make sense but I guess that's where all the token usage comes from? Pardon ramping up my skills via vibe coding this one idea for about a month and have never hit any quota and or have gotten anywhere near my limit.

[lettergram]

If you're self-hosting a model as a startup (e.g. using GPUs), you're almost certainly using a Chinese model. If your a startup outsourcing (e.g. using tokens), you're going to be using a US based model

[swiftcoder]

Particularly if Anthropic or OpenAI are throwing credits at you, which isn't that uncommon for US startups at the moment

[jdw64]

When developing AI services, Chinese models are cheaper. For the AI models used in actual services, like uploading an image and receiving a response, they use Chinese models.

On the other hand, when developers are developing, they mainly use US AI because the quality is better.

When developing AI related services, they prioritize Chinese models due to lower API costs.

It seems like the article didn't make this distinction.

So the claim that Chinese AI is the top choice for service level AI isn't entirely wrong.

[h2aichat]

May be corporations should start having their open models running in-house. There might be a huge oportunity there.

But the big price is AGI and who gets there first, right?

[no_wizard]

We aren’t getting anything like AGI in this current cycle of AI innovations.

At least not what I think most people imagine when someone says “advanced general intelligence”

Which is what we all called AI before the nomenclature goalpost moved

[igravious]

it's artificial general intelligence, not advanced. the point is that they'll be smart across the board at some point, super-intelligence is a whole separate issue.

[kccqzy]

It’s just not possible. FWIW my employer did not get onboard to the Cloud trend and continued to buy hardware for in-house data centers. But the kind of hardware needed to run sophisticated models are simply not for sale at the volume needed by a single company.

[apparent]

Assume you meant "big prize" but I guess it's sort of one in the same?

[lumost]

There is a big divide between “application ai” and “model ai” startups.

Model ai startups start from OSS models, and use them extensively for different purposes as their work would usually be banned by proprietary labs.

Application ai startups don’t want to fight the model game, so they either pick the best or let the user control it.

[danilocesar]

Not everything runs on paid models. Claude and Codex are frontier models, but some people have much higher usage needs and finite budgets that force them to self-host. And if you're self-hosting, you're very likely running a Chinese model

[apparent]

Especially if you're pre-funding, which the sampled startups (those pitching A16Z) were.

[syntaxing]

I don’t think they meant exclusively Chinese models. Many companies including the one I work for uses big US model for most of the work but data sensitive ones are on prem open source ones.

[embedding-shape]

Neither of you are clear on what exact location in the world you're sampling from here, could be you're both right, just missing that you're talking about different places.

[sacul]

I’m obviously a tiny, insignificant data point as a solo freelance dev, but I watch this space closely and I canceled my Claude Code subscription today.

[arjie]

It’s quite believable. Just a fact like “while all dogs breathe oxygen, all humans breathe nitrogen”.

[efficax]

the distinction may be between using the coding agents vs using models for products. for example where i work we're talking about dropping opus for a chinese model for the in-app agent (which is very expensive to run)

[airstrike]

yeah, I'm surprised I had to scroll this far to see this

everyone else seems to be thinking the quote is about AI-assisted coding but I read it as the model being used within the product itself

[dyauspitr]

What I’ve seen is coding is usually done with US frontier models and anything that is part of a feature on an app and runs at scale on the API is a Chinese model because they are dirt cheap.

[Someone1234]

That has been my experience too.

It will cost you more than it saves to use smaller Chinese models to code; because of the repeated work. That has been slowly changing recently, but with much larger Chinese models, however those models are so expensive they're much more price-competitive iwth the US competition.

But for actually providing end-user AI features, particularly simpler ones, the US isn't even in contention. The costs and limitations just outright kill those features conceptually.

[gs17]

That's what I lean towards with the exception that Gemma is also good on a lot of tasks and cheap, while not being Chinese.

[dyauspitr]

The problem is Gemma is actually not that cheap compared to deepseek for example

[rdtsc]

They are using both likely

[TheArcane]

anecdotal but we heavily use Qwen to build our own models on top of

[boondongle]

There appears to be a very Chinese strategy of astrotufing going on here similar to what happened with Douyin around TikTok on Reddit.

All of a sudden in almost all social media channels I'm seeing this type of content and then its usually upvoted to the top.

Non-gatekept forums like this are exceptionally easy to astroturf.

[chasd00]

Came here to post the same thing. I've noticed a lot of Chinese model astroturfing on HN over the past 60-90 days or so. Many upvoted posts in all conversations about AI touting how great the Chinese models are even when performance isn't the topic of discussion.