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 routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.
Apps using LFM 40B MoE
Top public apps this week using this model
Recent activity on LFM 40B MoE
Tokens processed per day
Uptime stats for LFM 40B MoE
Uptime stats for LFM 40B MoE across all providers
Sample code and API for LFM 40B MoE
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.