Audience
Developers interested in a 5 million token context window large language model
About LTM-1
Magic’s LTM-1 enables 50x larger context windows than transformers. Magic's trained a Large Language Model (LLM) that’s able to take in the gigantic amounts of context when generating suggestions. For our coding assistant, this means Magic can now see your entire repository of code.
Larger context windows can allow AI models to reference more explicit, factual information and their own action history. We hope to be able to utilize this research to improve reliability and coherence.
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LTM-2-mini
LTM-2-mini is a 100M token context model: LTM-2-mini. 100M tokens equals ~10 million lines of code or ~750 novels.
For each decoded token, LTM-2-mini’s sequence-dimension algorithm is roughly 1000x cheaper than the attention mechanism in Llama 3.1 405B1 for a 100M token context window.
The contrast in memory requirements is even larger – running Llama 3.1 405B with a 100M token context requires 638 H100s per user just to store a single 100M token KV cache.2 In contrast, LTM requires a small fraction of a single H100’s HBM per user for the same context.
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Company Information
Magic AI
Founded: 2022
United States
magic.dev/blog/ltm-1
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