Liquid: LFM 40B MoE

liquid/lfm-40b

Created Sep 30, 202432,768 context

$0.15/M input tokens$0.15/M output tokens

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.

See the launch announcement for benchmarks and more info.

Providers for LFM 40B MoE

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 300+ 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.