ByteDance: UI-TARS 7B vs LiquidAI: LFM3-1.7B
A side-by-side comparison of ByteDance: UI-TARS 7B ($0.35 / 1M tokens) and LiquidAI: LFM3-1.7B ($0.28 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| ByteDance: UI-TARS 7B | LiquidAI: LFM3-1.7B | |
|---|---|---|
| Provider | ByteDance | LiquidAI |
| Input | $0.35 / 1M tokens | $0.28 / 1M tokens |
| Output | $0.70 / 1M tokens | $0.70 / 1M tokens |
| Cache read | $0.35 / 1M tokens | $0.07 / 1M tokens |
| Context window | 128,000 | 262,144 |
| Max output | 2,048 | 8,192 |
| Input | image, text | text |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Jul 22, 2025 | Nov 6, 2026 |
Key differences
- LiquidAI: LFM3-1.7B is 20% cheaper on input tokens.
- LiquidAI: LFM3-1.7B reads 2.0× more context (262,144 tokens).
- Only LiquidAI: LFM3-1.7B supports tool calling.
- Only LiquidAI: LFM3-1.7B supports reasoning effort control.
- A request with 1,000 input and 500 output tokens costs $0.000700 with ByteDance: UI-TARS 7B and $0.000630 with LiquidAI: LFM3-1.7B.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "bytedance/ui-tars-1.5-7b" to "liquid/lfm-3-1.7b" 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": "liquid/lfm-3-1.7b",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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