LFM2.5-24B-A2B overview
LFM2.5-24B-A2B by LiquidAI
Send text messages, optionally with tool definitions, and receive a streamed reasoning response or structured JSON output.
LFM2.5-24B-A2B specs
- Model ID
liquid/lfm-2.5-24b-a2b- Developer
- LiquidAI
- Context window
- 128,000 tokens
- Max output
- 8,192 tokens
- Input
- Text
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
What Is LFM2.5-24B-A2B API?
LFM2.5-24B-A2B is an open-weight Mixture-of-Experts reasoning model developed by Liquid AI for fast, private agents running on-device.
The model always produces an explicit reasoning trace before its final answer and is post-trained for tool calling and multi-step agentic tasks.
Technical Reference
| Developer | LiquidAI |
|---|---|
| Model ID | liquid/lfm-2.5-24b-a2b |
| Release Date | October 13, 2026 |
| Context Window | 128,000 tokens (~128K) |
| Max Output Tokens | 8,192 tokens |
| Modalities | Text → Text |
| Capabilities | reasoning, streaming, structured (JSON schema) output, tool/function calling |
What LFM2.5-24B-A2B Brings to the Table
Sparse MoE design
The model has 24B total parameters with 2B active parameters per token.
Explicit reasoning
LFM2.5-24B-A2B always thinks before answering, using a <think> tag in its chat template.
Tool calling
The model supports tool calling and can interpret tool outputs before producing a final answer.
Open weights
The base and post-trained model versions are open-weight and available through Hugging Face and Liquid AI's Playground.
Where LFM2.5-24B-A2B Makes the Most Sense
On-device agents
Its sparse architecture and on-device focus make it suitable for private agents running on local hardware.
Multi-step automation
The model is post-trained for tool calling and multi-step agentic tasks.
Structured tool workflows
It can generate function calls, execute tool-assisted workflows, and return a final response based on tool output.
Sources: https://www.liquid.ai/blog/lfm2-5-24b-a2b · https://docs.liquid.ai/lfm/models/lfm25-24b-a2b · https://huggingface.co/LiquidAI/LFM2.5-24B-A2B
Use cases
Fast, private on-device agents that reason through multi-step tasks and call tools reliably, including agents running continuously on local hardware.
Knowledge-heavy applications that combine the model with retrieval or web search.
Local document-processing workflows, such as extracting text, comparing documents, and generating PDFs.
Security and compliance workflows, including scanning files for leaked credentials or personal data and producing audit trails for tool calls.
Capabilities
- Reasoning
- Streaming
- Structured outputs
- Function calling
LFM2.5-24B-A2B API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.1058 | 1M tokens |
| Output | $1.06 | 1M tokens |
| Cached input | $0.0529 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
LFM2.5-24B-A2B vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
| LFM2.5-24B-A2B | $0.1058 | $1.06 |
 DeepSeek V3.1 | $0.2857 | $1.06 |
| DeepSeek-V3.1 Terminus | $0.2857 | $1.06 |
| Weaver (alpha) | $0.7935 | $1.06 |
 Hermes 3 405B Instruct | $1.06 | $1.06 |
How to use the LFM2.5-24B-A2B API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "liquid/lfm-2.5-24b-a2b",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "liquid/lfm-2.5-24b-a2b",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "liquid/lfm-2.5-24b-a2b",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to LFM2.5-24B-A2B
LFM2.5-24B-A2B FAQ
How much does LFM2.5-24B-A2B cost?
LFM2.5-24B-A2B costs $0.1058 input and $1.06 output per 1M tokens on AI/ML API, billed as you go with no subscription.
What is the LFM2.5-24B-A2B model ID?
Use liquid/lfm-2.5-24b-a2b as the model parameter. Requests go to the OpenAI-compatible endpoint with your AI/ML API key.
What is the context window of LFM2.5-24B-A2B?
LFM2.5-24B-A2B accepts up to 128,000 tokens of context and returns up to 8,192 output tokens.