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Available now on ModelsLab · Language Model

LiquidAI: LFM2.5-1.2B-Thinking (free)Reason On-Device Free

Reason Smarter Faster

Chain-of-Thought

Generates Thinking Traces

Produces step-by-step reasoning before answers for math, logic, multi-step tasks.

32K Context

Handles Long Inputs

Sustains 46 tok/s at full 32K context for extended documents and workflows.

Agentic Power

Tool Use Optimized

Excels in planning tool calls, data extraction, RAG on LiquidAI LFM2.5-1.2B-Thinking free.

Examples

See what LiquidAI: LFM2.5-1.2B-Thinking (free) can create

Copy any prompt below and try it yourself in the playground.

Math Proof

Solve this equation step-by-step: prove that for all positive integers n, the sum of the first n odd numbers equals n squared. Show full reasoning chain.

Logic Puzzle

Three houses in a row, labeled A B C. A has red door, B blue, C green. Owners: Alice baker, Bob coder, Charlie engineer. Baker hates green. Coder in middle. Who lives where? Reason fully.

Code Debug

Debug this Python function that fails on large inputs: def factorial(n): if n == 0: return 1 else: return n * factorial(n-1). Identify recursion issue and fix with reasoning.

Data Analysis

Analyze sales data: Q1:100 units $10k, Q2:150 $15k, Q3:120 $12k. Predict Q4 trend, suggest actions. Use chain-of-thought for agentic planning.

For Developers

A few lines of code.
Reasoning API. One Call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
import requests
response = requests.post(
"https://modelslab.com/api/v7/llm/chat/completions",
json={
"key": "YOUR_API_KEY",
"prompt": "",
"model_id": ""
}
)
print(response.json())

FAQ

Common questions about LiquidAI: LFM2.5-1.2B-Thinking (free)

Read the docs

Ready to create?

Start generating with LiquidAI: LFM2.5-1.2B-Thinking (free) on ModelsLab.