32 posts tagged “deepseek”
DeepSeek is an AI lab from Chinese hedge fund High-Flyer.
2024
deepseek-ai/DeepSeek-V3-Base (via) No model card or announcement yet, but this new model release from Chinese AI lab DeepSeek (an arm of Chinese hedge fund High-Flyer) looks very significant.
It's a huge model - 685B parameters, 687.9 GB on disk (TIL how to size a git-lfs repo). The architecture is a Mixture of Experts with 256 experts, using 8 per token.
For comparison, Meta AI's largest released model is their Llama 3.1 model with 405B parameters.
The new model is apparently available to some people via both chat.deepseek.com and the DeepSeek API as part of a staged rollout.
Paul Gauthier got API access and used it to update his new Aider Polyglot leaderboard - DeepSeek v3 preview scored 48.4%, putting it in second place behind o1-2024-12-17 (high) and in front of both claude-3-5-sonnet-20241022 and gemini-exp-1206!
I never know if I can believe models or not (the first time I asked "what model are you?" it claimed to be "based on OpenAI's GPT-4 architecture"), but I just got this result using LLM and the llm-deepseek plugin:
llm -m deepseek-chat 'what deepseek model are you?'
I'm DeepSeek-V3 created exclusively by DeepSeek. I'm an AI assistant, and I'm at your service! Feel free to ask me anything you'd like. I'll do my best to assist you.
Here's my initial experiment log.
DeepSeek API introduces Context Caching on Disk (via) I wrote about Claude prompt caching this morning. It turns out Chinese LLM lab DeepSeek released their own implementation of context caching a couple of weeks ago, with the simplest possible pricing model: it's just turned on by default for all users.
When duplicate inputs are detected, the repeated parts are retrieved from the cache, bypassing the need for recomputation. This not only reduces service latency but also significantly cuts down on overall usage costs.
For cache hits, DeepSeek charges $0.014 per million tokens, slashing API costs by up to 90%.
[...]
The disk caching service is now available for all users, requiring no code or interface changes. The cache service runs automatically, and billing is based on actual cache hits.
DeepSeek currently offer two frontier models, DeepSeek-V2 and DeepSeek-Coder-V2, both of which can be run as open weights models or accessed via their API.