LiquidAI: LFM3-1.7B vs Meta: Muse Spark 1.3 Contributor
A side-by-side comparison of LiquidAI: LFM3-1.7B ($0.28 / 1M tokens) and Meta: Muse Spark 1.3 Contributor ($0.35 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| LiquidAI: LFM3-1.7B | Meta: Muse Spark 1.3 Contributor | |
|---|---|---|
| Provider | LiquidAI | Meta |
| Input | $0.28 / 1M tokens | $0.35 / 1M tokens |
| Output | $0.70 / 1M tokens | $0.70 / 1M tokens |
| Cache read | $0.07 / 1M tokens | $0.00700 / 1M tokens |
| Web search | - | $8.75 / 1K searches |
| Context window | 262,144 | 1,048,576 |
| Max output | 8,192 | 943,718 |
| Input | text | text, image, video, file |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Nov 6, 2026 | Sep 2, 2026 |
Key differences
- LiquidAI: LFM3-1.7B is 20% cheaper on input tokens.
- Meta: Muse Spark 1.3 Contributor reads 4.0× more context (1,048,576 tokens).
- A request with 1,000 input and 500 output tokens costs $0.000630 with LiquidAI: LFM3-1.7B and $0.000700 with Meta: Muse Spark 1.3 Contributor.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "liquid/lfm-3-1.7b" to "meta/muse-spark-1.3-contributor" 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": "meta/muse-spark-1.3-contributor",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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