“V4-Pro was engineered to cut the cost of long-context inference, reportedly running at roughly a quarter of the single-token compute and a tenth of the memory footprint of its predecessor at very long context. This is why the price cut is permanent rather than promotional. It is not a discount. It is an efficiency gain being passed through,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research.
DeepSeek narrows gap with Western AI rivals
Almost a year after introducing its R1 reasoning model offering performance and cost efficiency, DeepSeek released the preview of V4 LLM. Similar to the earlier models, even V4 is open source, which allows developers to download the code to run it locally and even modify it. The new models were optimized for use with popular agent tools such as Anthropic’s Claude Code and OpenClaw.
“From a pure capabilities perspective, DeepSeek V4-Pro has effectively closed the performance gap on critical tasks like complex math and reasoning, while aggressively leading the market on openness and inference costs. Its specialized reasoning modes and architectural enhancements make it a formidable alternative to Western frontier models,” said Neil Shah, vice president at Counterpoint Research. However, its primary limitations aren’t found in its raw intelligence; rather, it lags behind Western rivals on broader ecosystem adoption, global support structures, clear IP provenance, and the deep and secure hyperscaler integrations natively offered by AWS, Microsoft, and Google, he added.
Lower costs, better ROI
As inference costs remain one of the biggest barriers to scaling pilots into organization-wide deployments, DeepSeek’s aggressive discounts could translate into substantial savings for enterprises, say experts.
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