Dec 27, 2024 · Comprehensive evaluations reveal that DeepSeek-V3 outperforms other open-source models and achieves performance comparable to leading closed-source models. Despite its excellent performance, DeepSeek-V3 requires …

Jan 15, 2025 · A new model from Hangzhou upstart DeepSeek delivers outstanding performance and may change the equation for training costs. What’s new: DeepSeek-V3 is an open large language model that outperforms Llama 3.1 405B and GPT-4o on key benchmarks and achieves exceptional scores in coding and math.

Analysis of DeepSeek's DeepSeek V3 and comparison to other AI models across key metrics including quality, price, performance (tokens per second & time to first token), context window & more.

Jan 30, 2025 · With their V3 and R1 models, DeepSeek sets a new state-of-the-art in open-weight models and trades benchmark to benchmark with the best models from Anthropic, Google and OpenAI. The technical reports give detailed accounts of the architecture of the model, the trade-offs that led to it, and the efficient implementation that enabled their final training run to take a …

Jan 2, 2025 · DeepSeek-V3 represents a paradigm shift in open-source AI, delivering unmatched performance and efficiency. By integrating cutting-edge architectural innovations and training techniques, it narrows the gap between open-source and closed-source models.

Comprehensive evaluations reveal that DeepSeek-V3 outperforms other open-source models and achieves performance comparable to leading closed-source models. Despite its excellent performance, DeepSeek-V3 requires only 2.788M H800 GPU hours for its full training.

Dec 26, 2024 · DeepSeek-V3 is built on a Mixture-of-Experts (MoE) architecture and boasts a substantial 671 billion parameters, with 37 billion parameters actively engaged during inference. The model was trained on a massive dataset of 14.8 trillion tokens, contributing to …

Jan 17, 2025 · DeepSeek has recently released DeepSeek v3, which is currently state-of-the-art in benchmark performance among open-weight models, alongside a technical report describing in some detail the training of the model. Impressively, they’ve achieved this SOTA performance by only using 2.8 million H800 hours of training hardware time—equivalent to about 4e24 FLOP if …

Dec 26, 2024 · Comprehensive evaluations reveal that DeepSeek-V3 outperforms other open-source models and achieves performance comparable to leading closed-source models. Despite its excellent performance, DeepSeek-V3 requires …

Dec 26, 2024 · DeepSeek claims that DeepSeek V3 was trained on a dataset of 14.8 trillion tokens. In data science, tokens are used to represent bits of raw data — 1 million tokens is equal to about 750,000 words.