How DeepSeek’s new AI models are impacting the profits of global companies
China’s DeepSeek shook global stock markets after revealing that it had built a powerful artificial intelligence model for a mere $6 million. While some have disputed the shockingly low cost of developing the AI models, most agree that DeepSeek has sharply cut the on-going cost of running powerful AI models and that the firm’s decision to release its technology for free has altered the course of the industry. CNBC Pro spoke to companies around the world on how DeepSeek’s new AI models are set to impact their operations and financials. Roadzen , a Nasdaq-listed company, is attempting to disrupt the auto insurance sector with artificial intelligence. The company’s AI service helps its insurance underwriting clients to cut the time taken to resolve 80% of minor accident claims from six weeks to two minutes, according to its chief executive Rohan Malhotra. The sensitive nature of processing insurance claims, alongside the potential for incorrectly predicting large costs for insurance clients, means the company has previously limited itself to a handful of sophisticated AI models that produce accurate results — such as those produced by OpenAI, Anthropic and Meta . That was until DeepSeek released its R1 model. “Our clients cannot afford a model which has 60%-70% accuracy, that’s like a major economic issue,” said Malhotra. “We need to deploy models that have 95%-99% accuracy.” DeepSeek’s discount Malhotra, who graduated with a master’s degree in robotics from Carnegie Mellon University, said DeepSeek-R1 output quality is on par with OpenAI’s o1 — its best large language model — while also offering other benefits that are significant to his company, including costs. For instance, Roadzen processed 607,577 insurance claims for the three months ending September 2024. Each claim consumes roughly 4,000 tokens, according to the company. A token is the smallest unit of data fed to an AI model. About 750 words converts to 1,000 tokens. The AI firm would have incurred a cost of $36,455 over the quarter using OpenAI’s latest large language model o1, according to CNBC calculations using publicly available pricing. That means on average, the company spent 6 cents per claim on AI costs. However, using DeepSeek-R1, the quarterly cost of $17,012, calculated using prices from AI model hosting firm Together.ai, would amount to 3 cents per claim, or 50% lower than costs incurred with OpenAI’s models. Roadzen revealed that the firm incurs additional costs when fine-tuning or training an AI model on a per-policy basis, which would have amounted to $21,185 using the OpenAI o1 model, or $10,593 on DeepSeek’s R1. In addition, it also faces additional costs to run its proprietary AI models that are used to estimate the cost of claims, detect vehicle damage over video and for fraud prevention among other uses that are not covered by commercially available models. “What we really care about is the cost of inference. We care about the accuracy of the outputs. And we care about whether this model is performing to the certain benchmarks that we’ve set, in a good way,” Malhotra added. The open-source innovation Others have told CNBC that alongside the lower costs, DeepSeek’s landmark decision to open source its reasoning model makes it more attractive compared to existing open-source models like Meta Platforms’ Llama. Arli Charles Mujkic, CEO and founder of Swedish AI platform Ooda AI, told CNBC his company integrated DeepSeek’s technology into its AI offering “the same day it was out.” The company runs a digital store that offers customers a choice of AI models, allowing them to choose the best app for a specific job. Ooda AI has various revenue sources within the business: it sells pay-per-month subscriptions to AI apps on its store, allows customers to pay a base fee for AI programs and usage tokens, and also offers fixed-term contracts to its enterprise clients. Mujkic said his opinion of DeepSeek’s v3 large language model — the technology that underpins its products — is that it’s up to 20% “better” than Meta’s Llama 3.3, which he labeled “the best open source model we’d been running up until this point.” Ooda AI, which boasts one of Germany’s largest health insurance firms as a clients, said it costs roughly 1.875 U.S. cents per customer support issue, or $18,750 per million, to be resolved using open-source AI models. However, the same tasks are likely to be 32% cheaper when executed on DeepSeek’s AI models, according to the company. The company, whose Stockholm-listed shares have gained more than 1,400% over the past year, is expecting DeepSeek’s AI models to lower its costs — and ultimately boost its revenues. G7H0-FF 1Y line “It’s 35% cheaper [than models like Llama], which means ultimately, for us — without changing any pricing, say on the enterprise side — we start making 35% more money,” he told CNBC. “But also for our customers, who are paying for AI compute, for example, it becomes 35% cheaper as well, because that goes in parallel with the pricing for token users.” DeepSeek’s R1 reasoning model is also “on par” with OpenAI’s o1, Mujkic argued, while running as much as 80% cheaper. “This is the kind of paradigm shift that’s happening now,” he said. Neal K. Shah, CEO of North Carolina-based eldercare platform CareYaya, also told CNBC his company — which has started using AI to help customers fight health insurance claims denials — was excited about DeepSeek. “DeepSeek just lowered our costs by 90% so we can help more people,” he said in a message. “The average cost to appeal a U.S. health insurance claims denial is $43.84. We had used OpenAI and Anthropic to get the cost down to 12 cents — now we’re doing it with DeepSeek on the back end, the cost per appeal is 2 cents.” Asked if DeepSeek would boost CareYaya’s bottom line, Shah’s immediate response was “yes.” “It’s a ridiculous step function in lowering costs,” he explained. “We’ll pass along a lot of the savings to the consumer, so it’ll let us serve more people.” AI’s negligible costs Despite the cost of AI falling substantially over the past two years, companies do not expect the cost of rendering AI services to end users to fall at the same rate. Roadzen’s Malhotra suggested that AI costs are a tiny fraction of the roughly $150 per claim it charges its insurance clients in Western markets. The bulk of its costs are spent on research and development and connecting legacy systems at large enterprises with its AI systems. However, he expects lower AI costs in the future could enable automation in emerging markets, where labor costs are still competitive with AI systems today. “As a global company, the $150 may be a price for a highly developed market. When we lower the inferencing cost enough, we can now deploy it globally,” Malhotra added.
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