Chinese AI Competition

Debates about DeepSeek and other Chinese models offering comparable quality at lower prices, concerns about data privacy, open-weight models enabling US/EU hosting, and potential market disruption

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The emergence of Chinese AI models like DeepSeek and Qwen has ignited a fierce debate over whether US frontier labs can maintain their high-margin dominance as intelligence rapidly becomes a commodity. Many users argue that these "good enough" models offer massive cost savings that could disrupt the industry, sparking theories that China’s aggressive pricing stems from superior hardware efficiency and cheap energy rather than mere government subsidies. While security concerns persist regarding data privacy, the release of high-quality open-weight models allows Western developers to host these tools on trusted local infrastructure, effectively sidestepping "phoning home" risks while putting immense financial pressure on American firms. Ultimately, this competition highlights a growing strategic divide: a potential global race to the bottom in token pricing that may eventually force the US to choose between out-innovating on cost or utilizing legislative bans to protect its domestic AI market.

71 comments tagged with this topic

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> I noted that my own token usage comes to about $1,000/month against each of Anthropic and OpenAI - which currently costs me just $100 per provider thanks to their generous subsidized plans for individual subscribers. Do we know that AI providers are going to keep these per-token prices, or eventually lower them because of competition from China? Many lower-budget individuals are now moving to China open weight models like DeepSeek. I wonder if China's really subsidising the providers, or if inferencing costs are actually much lower, and Anthropic/OpenAI are just making sure no money's left on the table for their eventual IPOs.
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We can tell that the inferencing costs for many of these models are low enough that these models are being sold close to real costs on the basis that many of them are open weight and available from third party providers who have no incentive to subsidize them. I think the frontier labs will need to drop their high per-token prices at least for their low and mid-level models for the reason that several Chinese models (at least Qwen, DeepSeek, Kimi and GLM) are "close enough" that with the right harness they are cost effective alternatives. They won't necessarily need to close the gap - at least not yet -, because these models won't necessarily compete at the same token counts . E.g. at least some of them need to do far more work to solve the same problems. But, yeah, the prices will come down one way or the other. At the same time, even the subscriptions for the cheap Chinese models are probably subsidised, and those subscriptions are likely to get less generous over time.
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I really doubt Deepseek is subsidised. It's roughly the same price everywhere you look. Deepseek is using the Huawei hardware (as far as I managed to understand from various articles) and hence the savings.
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And Chinese electricity prices are some of the lowest
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Add MiMo 2.5 to the list. Priced like DeepSeek, performs similarly but it also has vision capability.
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A few things, I think you’re missing the point here - most tasks do not require the latest frontier models, even if they are a magnitude more intelligent (we don’t actually know if that will be the case). Current Gemini flash is cheap, fast, and pretty capable with good guidance for most tasks - now that companies pay API costs instead of a subscription they will be setting restrictions on token use to not have their budget explode (like Uber in this submission), that’s a strong incentive to NOT use expensive models, and limit their thinking budget - there is competitive pressure from China and others who can offer very decent performances at a fraction of the token price - the price of tokens for the frontier models is likely to go up, but the price to access older models is what depreciates! The overall price per token is going down now that we are in a new world where companies understand that token maxing is one of the stupidest concept ever created by humankind.
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When everything is said and done it'll be datacenters in American competing with ones in China that have several times lower electricity prices. Token prices will drop to a level that will be unprofitable for American data centers and they will need to close. Thats the main issue here.
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I sometimes let Claude Opus create plans, DeepSeek v4 pro implements and writes tests. Claude reviews and corrects. Saves like $2-3 per session. Same quality code.
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Don't worry, they'll just lobby to ban Chinese models instead to keep their token revenues high. > Compounding the problem, labs in China often release dual-use capable models as open-weight. Once a model is open-weight, safeguards that do exist can be removed, making the model available to any state or non-state actor to use for malicious purposes, including the cyber and CBRN misuse those safeguards were built to prevent. https://www.anthropic.com/research/2028-ai-leadership
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If you do the math, they don't have a choice. If China captures America's AI market it'll cause a major depression. They'll give it the BYD treatment, though it'll be a lot less effective.
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They'll ban them because (unless run locally or self-hosted) they are just data capture tools for the China.
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If it’s open weight then anyone can run it for you. Presumably someone you trust just as much as US proprietary models.
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I don't think they'll offer open models for long. Since they've actually invested in power, cheap chips, cheap memory and can subsidize tokens - they'll keep undercutting big models to capture data forever. Bonus if they remove ridiculous safeguards and China will be unstoppable.
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Pretty sure they'll offer them at least so long as it takes to bring OpenAI and Anthropic into insolvency. Why wouldn't they? The Chinese models are way more nimble to train and run, bring in a ton of goodwill globally, and put immense pressure on the VC furnace that is the US AI sector. And apparently OpenAI and Anthropic think so, too - why else would they try so hard to ban them instead of outcompeting them?
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Please explain to me how that works. If I download gguf file and run inference with it, how is it collecting and sending data back to China? This makes no sense, 99% of the people using Chinese models are using them via Western inference providers who are running them and serving them to people over openrouter or whatever. If anyone is stealing your data it would be an American or European inference provider. A model has no ability to send data anywhere. China bad by default, right?
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You will see soon that china uses illegal uyghur children labor to train these models so we should all boycott them
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> Once a model is open-weight, safeguards that do exist can be removed Safeguards trained into the model (ie exist in the weights) can’t be removed.
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You don't have to remove the safeguards if you can prompt your way around them. There's a subreddit for people wanting to sex-talk to various models. It just so happens that the same prompt they use to 'jailbreak' SOTA models for sex talks also works if you want to have model write malware, or tell you how to design a highly illegal device.
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China is the worst trading partner in the world. They banned most companies from functioning in their country for decades
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So, have you ever been to China and could hadely found anything familay? - Oh, they must have been blocked from entering the Chinese market! But none of that is true. You could see global brands everywhere here — Tesla, Unilever, KFC, Apple, and so on. --- Or have you ever actually done cross-border trade? Or any international business collaboration? If you had, you’d definitely realize that what’s really stopping you is U.S. legislation. At least, that was the case with our former U.S. partner
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Have you ever heard forced IP transfer and partnerships?
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One-Drop Rule + Long-Arm Jurisdiction = Everything eventually comes under US control. That's what I see, don't need to 'hear' it from Why even bother with 'forced IP transfer' when you can just take it?
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Why would I even pay for deepseek? I get deepseek v4 flash for free with opencode. If I somehow run out of tokens for the day, I can just then on my vpn
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Most sane US companies will disallow use of cloud-based Chinese AI providers, because everything including code, data, PII, etc is being sent to them.
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Then don't use the cloud-based Chinese providers, use cloud-base US/EU providers using Chinese models. The interesting Chinese models are all open making this issue mostly moot.
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A key point here is open in terms of being able to download and use it, not open as knowing what data and instructions were fed into it when training. A paranoid part of me thinks that these models are all inherently biased and instructed to be pro CCP, with specific gaps in their training data related to undesirable historic events and political ideas.
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The same thing applies to US models. Check out various system prompt leak repos on github. There are also prompt injections by various parallel "alignment" models that pre-process the prompt before it's sent to the main one with questionable guidance. You'd be surprised how much of bias exists in easily extractable information. Now imagine how much of that happens during training, that you can't easily extract. So this is largely a moot point. Yes, Chinese models will likely have some weird things injected into them. But so do the US models. Do I care? Not in the slightest. Models are my code monkeys, and if the code leaves my machine, I assume IP is leaked be it a Chinese model that clearly tells me they do use the data, or US models that pinky promise they don't.
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Sure but that goes both ways. Any dataset has a bias. My coding doesn’t need to know about Tienamen square.
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Applies both ways, ask it about Israel.
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Saner companies ask the same question about models from their own country too.
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I wonder if I could start a US-based company with good data regulation and just serve open-weight models at a competitive price. I feel like the real barrier is just that most companies willing to adopt AI usage enough to make it worth it at this point don't want to be using inferior models.
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Here's a free startup idea: operate an open-weight model service, and offer "Verified AI Integrity," which signs the input tokens, the seed for the randomness in selecting outputs, and the model ID, proving that the result of the call to AI was completely "organic" and was not interfered with. Your main audience would be snake oil salesmen trying to prove their AI products are unbiased and not under the thumb of any outside influence. This doesn't address the biases of the model itself, but that's not your business. Your business is selling tokens and security certificates. If you can get the right angel investor, you could maybe have your new standard required for some government applications.
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Yes, you can. There are multiple inference providers out there. The problem is, it’s hard to beat the Chinese providers in cost. And you also have to compete with frontier model providers’ subsidized offerings.
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They charge the exact same prices. So many people in these comments have no idea what they're talking about. Even if they did charge less, nobody is going to deal with the latency of sending requests to China. edit: Actually American inference providers are cheaper for Chinese models. There's way more competition here because the Chinese aren't idiots and investing every last dollar they have into data centers for llms that don't make money..
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Can you please link me DeepSeekV4 provider that's cheaper than their official offering? And not all tasks require low latency. Also, there are a lot of competition in China. Like a lot. You might know better than me as well, but although the biggest AI-labs are based in USA, the adoption is weirdly global. Like as a general sense of what's going on - you can see AI-related ads literally everywhere in Tokyo, almost all the time, in every single screen in public.
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Cro.ai seems to be: https://crof.ai/ Of course though they are not necessarily a viable solution for companies with security requirements etc. given it is just a single person project, but they still serve as a proof it can be done.
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Deepseek's api platform for V4 Pro is the only example of this, and Deepseek V4 Flash is cheaper (usually) than from Deepseek itself on openrouter via DeepInfra. Deepseek shot themselves in the foot because they never intended to serve V4 Pro for .80c mm ouput, that was a promotional price that was meant to expire (and still might). They intended for v4 to cost $4.00 per million but Western inference providers drove down the price because they can operate at negative margins to try and push competition out. I can assure you they are losing a ton of money @ ~80cents. My point is, its Western inference providers that are establishing the floor price of inference. They are willing to operate at a loss in order to put their competition out of business. Chinese providers are typically at or above the prices set by American/western providers if you go looking on the Chinese internet. You aren't going to get deals from China for inference except through this one instance with Deepseek v4 Pro which wasn't even supposed to be permanent pricing.
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By "cost" I think the parent means the provider's own costs, not the cost of inference to the customer. The cost of land, labor, and electricity are significantly lower in China than in the US.
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There are plenty of US-based inference providers available, including AWS, that serve Chinese models at competitive prices (vs frontier US models). They also have lots of usage. Not necessarily for coding, but for other enterprise tasks.
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Have you heard of openrouter? There's 1000 of these companies already. Do something else.
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It's called AWS. Bedrock is right there. Price or data policy is never the issue. The models themselves are the problem -- most large US companies are not going to touch them. Source: directly involved in these discussions. You can downvote as much as you'd like but you can't ignore the facts.
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Some suits with no understanding of how LLMs work are scared that the models might hack them, or believe that they'd have to send data to China because they do not know that open models can be run on your own infra.
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You can run DeepSeek as it's open weights, unlike Claude or GPT.
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There are some objections here saying that some US firms are using Chinese AI providers, but I wonder if any of those are subject to compliance. Large firms that are disproportionately responsible for AI spending are all subject to compliance.
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Deepseek has some models in Bedrock. There is definitely a huge market for a "good enough" model running within the country of the company
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> Deepseek has some models in Bedrock. Just looked into it, seems like at most they have just 3.2, not 4: https://aws.amazon.com/bedrock/pricing/ Looking around their catalogue more, most of their models seem quite outdated, aside from the OpenAI and Anthropic ones (but those get more expensive). I wouldn't willingly pick Bedrock and would instead throw money at OpenRouter, that has both a bunch of providers, as well as almost any model for you to try.
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id be amazed any american business will aend data to china
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HuggingFace offers DeepSeek as one of its models— it's pretty simple to spin up instances under your control. I'm not sure about OpenRouter but I wouldn't be surprised if they offer a US-based provider of DeepSeek. For reference, Cursor has their first own light fork of Kimi that they use as their baseline coding and review model.
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The majority of Deepseek providers on OpenRouter for v4 pro are in the US. Especially interesting is that they are in the same ballpark for pricing.
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They are in the same ballpark for deepseek-v4-flash, but deepseek-v4-pro from deepseek is still around 1/2 of the alternatives.
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I'm pretty sure that Deepseek said that pricing was promotional. Be curious to see if it lasts. V3 pricing from them was right in line with what the commodity providers are charging.
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They announced a few weeks back that the promotional pricing was permanent.
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“Any” is a very high bar Unless laws prevent it, I don’t see why a substantial minority wouldn’t buy services from where they can get them at a similar quality and much lower price.
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Together.ai provide many open weights models and as far as I’m are their servers are US based (the company certainly is)
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Any IT cost center will send to the lowest bidder. This isn’t intellectual property: it’s annoying shit that is an unwelcome cost of doing business. China might copy our tedious scripts? Will they make a product out of it? Can I buy it and fire my IT staff? Great! Not everyone using AI is using it to code core value IP.
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API prices of Anthropic, OpenAI, and Google are massively inflated. https://martinalderson.com/posts/no-it-doesnt-cost-anthropic... There's no way that all AI inference providers are colluding and/or all running at a massive loss, meaning the cheap Chinese model prices must be the real cost it takes to run frontier-class models PLUS their margin. Look at Deepseek 4 Pro. https://openrouter.ai/deepseek/deepseek-v4-pro/providers Deepseek and Baidu are subsidising prices but they probably train on inputs. I have no model training and ZDR in OpenRouter enabled, and the first provider that shows up there is Deepinfra, significantly more expensive than Deepseek. BUT much cheaper than Sonnet 4.6 and ChatGPT GPT-5.4.
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Many harnesses do this, I've recently dropped all my big subscriptions for using deepseek. Codewhale (formerly deepseek-tui) will use pro for large tasks and route smaller ones to flash. It's pretty good, but I just use pro and everything as the cost is quite low. This one does not have routing, but reasonix is insane, absolutely insane for saving money. I've used 1.3billion tokens at the cost of 4$. (99-100% cache hit)
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Infrastructure is massively complex and multi cloud is super hard to do. Switching LLMs is... a drop down. Now, that doesn't mean running your own LLM will be easy, but this will mean it's a lot more likely that there will be at least regional LLMs, in my opinion. I.e. there will be Google, whichever (if any) is left standing of OpenAI or Anthropic, and then there will be Chinese hosted LLMs, probably Indian hosted LLMs, European hosted LLMs, plus LLMs hosted on managed services (i.e. Bedrock). For sure I see large banks on the like being able to host the best OSS or even licensed LLMs on their own cloud infrastructure accounts (i.e. at AWS, Azure, etc). And that's on top of the LLMs running on owned server infrastructure plus actual local, on device LLMs.
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Second here. From recent Alibaba Qwen conference: the all-in-one box (DC in a box - I think I was called Apsara, 0.6x0.6x1.5m) plug and play, 1.5TB GPU RAM, capability to run in a fully air gapped environment, any open models... All of that is roughly $300k one time. And this box can do non LLM tasks as well. Performance (throughput) around 20k t/s. Delivery time - around 2 months. For any medium sized company its perhaps cheaper to just buy it once than spending 1.5k for cloud per user
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How is tok/s not a bottleneck I? I assume most people still use ai agents interactively rather than leaving them to do their own thing during the night. I find anything below 50 tps or so entirely unusable... Regardless its Apples to oranges anyway, inference is quite cheap for open weight models its just that Claude and OpenAI can charge very high margins compared to e.g. DeepSeek or various provider on OpenRouter since open models are a commodity.
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128GB machines can't run anything locally that is even nearly as capable as a frontier model like Claude. We can get an idea from deepseek v4 pro being 1.6T model, requiring approx. 860GB VRAM to run.
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I don't think they'll have a choice, open weights models are not far behind. At some point it's essentially a commodity game
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Openrouter? i.e. Even excluding Deep Seek inference for very large open models is way cheaper. Maybe these providers are not very profitable but its highly unlikely that they are losing $4 for every $1 they make since selling inference is their only product...
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It's mostly R&D though, not inference. If LLM's effectively become a commodity then they are screwed anyway.
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Aren’t the Chinese labs quickly turning them into a commodity? The open-weight models will have a steady race to the bottom on inference costs just by dint of competition between providers. They aren’t at the frontier yet, but they are rapidly eating the flash market.
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Yeah, that's not going to work if you can get e.g. 80% of value by using 10-20x or more cheaper open models. At some point it would just make sense for large companies to rent compute and deploy their version of DeepSeek or whatever (if they don't trust Chinese providers)
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The inference prices for very large open models would indicate that Antrophic's and OpenAI's margins are quite large.
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Seems odd limit, especially since it highly dependant on Token provider used, with Opus this is not much and could easily be burnt in a week or less, but with something like deepseek the 1500 can literarily be an annual budget. That being said, I do have to wonder why someone as bug as say Uber, simply not rollout OSS model in the cloud for their team, I'd imagine that would be cheapest & most flexible option, while also keeping all the data shared with LLM private.
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eventually tokens will cost price of energy. and china is miles ahead. china will be major token exporter soon. mark my words.
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If china captures the market now, well deserved. Way cheaper compared to us providers.
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China will bring down the price per million tokens.