DeepSeek's New Model Nearly Matches GPT-6 Astra on Design—at 1.4% of the Cost
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GPT-6 Astra Users Say OpenAI's Newest Model Got Dumber. It Happened Before, Too
A week after launch, complaints are rolling in from users that GPT-6 Astra has been nerfed. OpenAI's last model went through the same cycle in July.
Analysis: To reduce costs, overseas developers are turning to Chinese AI models such as DeepSeek.
According to Odaily Odaily, as the cost of using AI continues to rise, more and more overseas startups and developers are adopting Chinese AI models such as DeepSeek, Alibaba, and Moonshot AI to reduce inference costs. Data shows that DeepSeek's share of AI traffic on the cloud platform Vercel has increased from less than 1% in May of this year to 17%. OpenRouter, an AI model aggregation platform, stated that DeepSeek's usage doubled in the first half of 2026, becoming the platform's most popular model. It also pointed out that the token usage share of Chinese open-source models, including those from Xiaomi, MiniMax, and Tencent, continues to rise, while the share of Google and OpenAI has declined. (Bloomberg)
OpenAI Releases GPT-6 Astra: The Closest AI Model Yet to AGI
The model can independently discover and exploit unknown security flaws across hardened systems, triggering a staged rollout and White House review before public access.
Some large-scale AI models in China are 90% cheaper than those in the US; Chinese AI's high cost-effectiveness is capturing the US market.
According to a report by CNBC on July 7th, influenced by the continued price increases of models from leading US AI vendors, Chinese AI large-scale models are rapidly expanding their application scale in US enterprises due to their cost-effectiveness advantage. Industry insiders point out that the performance of some leading open-source and open weighted models in China is currently about 6 to 9 months behind the technology of top-tier US models such as OpenAI and Anthropic, while the price is 60% to 90% lower, and they can cover the vast majority of routine AI tasks, thus gaining popularity among US enterprises. According to statistics from the AI model aggregation platform OpenRouter, since February 8th of this year, the proportion of Chinese AI models used by US enterprises has exceeded 30% weekly, reaching a peak of 46%; while the average proportion in the previous 12 months was 11%. Another industry statistic shows that in the first week of the launch of Zhipu's latest large-scale model GLM 5.2, the daily average number of word calls increased by 27 times and the number of customers increased by 80 times, making it the fastest-deployed model on the platform in 2026; US AI startup Lindy has significantly reduced costs after switching all its AI business to DeepSeek models, and expects to save millions of dollars within a few months. (CCTV Finance)
Gu Yuxian, a Tsinghua University Special Scholar, joined DeepSeek, where he previously led the development of large-scale model distillation and a 50x speedup for long text processing.
According to Beating's monitoring, Gu Yuxian, a PhD graduate from the Department of Computer Science at Tsinghua University and recipient of the 2025 Graduate Special Scholarship, has officially joined DeepSeek, and his name has appeared in the author list of the DeepSeek V4 paper. Gu Yuxian's research mainly focuses on efficiency optimization of large models in the pre-training, model compression, and inference stages, and has been cited nearly 5,000 times on Google Scholar. Gu Yuxian's previous representative works include the knowledge distillation method MiniLLM for large models (which has been adopted by platforms such as Google, Alibaba, and NVIDIA), and the hybrid architecture model Jet-Nemotron. Jet-Nemotron achieves a 53.6 times faster throughput than traditional full-attention models when processing 256K ultra-long contexts on an H100 GPU, and surpasses hybrid expert models with larger parameter scales in multiple benchmark tests.
DeepSeek's Secret Self-Developed Inference Chip
According to Beating, Reuters, citing sources familiar with the matter, reports that DeepSeek, a major Chinese model-making company, is developing its own AI inference chip. This research began about a year ago and is primarily for model inference rather than training. In recent months, the company has been privately recruiting chip design engineers. Currently, DeepSeek's model operation and training heavily rely on chips from Nvidia and Huawei. If successful, developing its own inference chip would reduce reliance on external suppliers and provide more cost-effective hardware control. However, the project is still in its early stages and faces manufacturing and memory access restrictions due to US export controls.