LiquidAI: LFM2.5-2.6B vs Qwen2.5 72B Instruct
A side-by-side comparison of LiquidAI: LFM2.5-2.6B ($1.22 / 1M tokens) and Qwen2.5 72B Instruct ($1.26 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| LiquidAI: LFM2.5-2.6B | Qwen2.5 72B Instruct | |
|---|---|---|
| Provider | LiquidAI | Qwen |
| Input | $1.22 / 1M tokens | $1.26 / 1M tokens |
| Output | $1.75 / 1M tokens | $1.40 / 1M tokens |
| Cache read | $0.14 / 1M tokens | - |
| Context window | 128,000 | 32,768 |
| Max output | 8,192 | 16,384 |
| Input | text | text |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Aug 11, 2026 | Sep 19, 2024 |
Key differences
- Both have about the same input price.
- Qwen2.5 72B Instruct is 20% cheaper on output tokens.
- LiquidAI: LFM2.5-2.6B reads 3.9× more context (128,000 tokens).
- Only LiquidAI: LFM2.5-2.6B supports reasoning effort control.
- A request with 1,000 input and 500 output tokens costs $0.00210 with LiquidAI: LFM2.5-2.6B and $0.00196 with Qwen2.5 72B Instruct.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "liquid/lfm-2.5-2.6b" to "qwen/qwen-2.5-72b-instruct" and prompts, streaming and tools keep working.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.chat.completions.create({
"model": "qwen/qwen-2.5-72b-instruct",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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