An analysis of 100T+ tokens from the past year shows reasoning models now represent over half of all usage, open-weight model use has grown steadily, and more
this is not a model I hear much about. [image] @openrouterai : We collaborated with @a16z to publish the **State of AI** - an empirical report on how LLMs have been used on OpenRouter. After analyzing more than 100 trillion tokens across hundreds of models and 3+ million users (excluding 3rd party) from the last year, we have a lot of [image] @a16z : >100 trillion token analysis of reasoning model usage over time Full piece from @MaikaThoughts, @AnjneyMidha, @xanderatallah, and @cclark: https://openrouter.ai/... [image] @scaling01 : The moment open-source models were close to 30% of OpenRouter traffic and almost all of them came from China with the notable models being: DeepSeek V3/R1, Qwen3 family, Kimi-K2 and GLM-4.5 + Air Minimax M2 is now also a major player, but open-weights models token-usage [image] Nathan Lambert / @natolambert : On a prompt count basis this mean reasoning models are not close to a majority on OpenRouter, as reasoning models can use 10-1000x the tokens of non-thinking models per prompt. Lots of need for fast, efficient open models. Reasoning model usage is likely closed labs more. [image] Bluesky: Tim Duffy / @timfduffy.com : Lots of interesting details in this new report on usage trends from OpenRouter. openrouter.ai/state-of-ai I've been wondering about mean coding input token length, in their data it's around 20k tokens. Other large categories (roleplay, technology science) average around 5k [image]