A new rising star has emerged in India's artificial intelligence field. The large model Alpie released by 169PI company has shown outstanding performance on multiple international mainstream AI rankings, even surpassing GPT-4o and Claude3.5 in some mathematical and software engineering metrics, earning it the nickname "DeepSeek of India" within the industry.
Despite being a small-scale model with only 32 billion parameters, Alpie's actual test data is astonishing. On the GSM8K ranking, which measures mathematical ability, its performance not only exceeded DeepSeek V3 but also matched up with GPT-4o. In the SWE ranking, which evaluates software engineering capabilities, it outperformed top models like Claude3.5, demonstrating strong logical processing capabilities.
However, the impressive scorecard comes with considerable controversy. Technical analysis shows that Alpie was not entirely trained from scratch by the Indian team, but rather is a secondary development based on the Chinese open-source model DeepSeek-R1-Distill-Qwen-32B. In other words, it is a product of "distillation and quantization" applied to a Chinese open-source base model.
Although it has been criticized as "a shell," Alpie has significant commercial value. Through 4-bit quantization technology, this model significantly lowers the entry barrier, reducing VRAM usage by 75%, and can run smoothly on consumer-grade GPUs with 16-24GB of memory. This "high cost-performance" approach makes its inference cost just one-tenth of GPT-4o, offering a highly competitive option for small and medium-sized developers.
Key points:
🚀 Ranking standout: Alpie performs well on mathematical (GSM8K) and software engineering (SWE) rankings, with some performance metrics even surpassing GPT-4o and Claude3.5.
🧬 Technical source: The model was not self-developed, but rather a deep secondary development based on the Chinese open-source large model DeepSeek, essentially an open-source technology distillation and quantization version.
📉 Very low threshold: Thanks to 4-bit quantization technology, Alpie has reduced inference costs to one-tenth of mainstream models, and supports smooth deployment on consumer-grade GPUs.
