Liquid's 40.3B Mixture of Experts (MoE) model. Liquid Foundation Models (LFMs) are large neural networks built with computational units rooted in dynamic systems.
LFMs are general-purpose AI models that can be used to model any kind of sequential data, including video, audio, text, time series, and signals.
OpenRouter normalizes requests and responses across providers for you.
OpenRouter provides an OpenAI-compatible completion API to 0 models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.
In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.
from openai import OpenAI
client = OpenAI( base_url="https://openrouter.ai/api/v1", api_key="<OPENROUTER_API_KEY>",)completion = client.chat.completions.create( extra_headers={"HTTP-Referer":"<YOUR_SITE_URL>",# Optional. Site URL for rankings on openrouter.ai."X-Title":"<YOUR_SITE_NAME>",# Optional. Site title for rankings on openrouter.ai.}, extra_body={}, model="liquid/lfm-40b", messages=[{"role":"user","content":"What is the meaning of life?"}])print(completion.choices[0].message.content)
Using third-party SDKs
For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.
See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.