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Muse Spark 1.3 Contributor vs Nemotron 3 Nano 30B A3B: API price, context & features · api14

Meta: Muse Spark 1.3 Contributor vs NVIDIA: Nemotron 3 Nano 30B A3B

A side-by-side comparison of Meta: Muse Spark 1.3 Contributor ($0.35 / 1M tokens) and NVIDIA: Nemotron 3 Nano 30B A3B ($0.21 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Meta: Muse Spark 1.3 Contributor	NVIDIA: Nemotron 3 Nano 30B A3B
Provider	Meta	NVIDIA
Input	$0.35 / 1M tokens	$0.21 / 1M tokens
Output	$0.70 / 1M tokens	$0.84 / 1M tokens
Cache read	$0.00700 / 1M tokens	$0.04 / 1M tokens
Web search	$8.75 / 1K searches	-
Context window	1,048,576	262,144
Max output	943,718	235,929
Input	text, image, video, file	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Sep 2, 2026	Dec 14, 2025

Key differences

NVIDIA: Nemotron 3 Nano 30B A3B is 40% cheaper on input tokens.
Meta: Muse Spark 1.3 Contributor is 17% cheaper on output 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 $0.000700 with Meta: Muse Spark 1.3 Contributor and $0.000630 with NVIDIA: Nemotron 3 Nano 30B A3B.

In depth

Meta: Muse Spark 1.3 Contributor is a text model from Meta, released on 2 September 2026. NVIDIA: Nemotron 3 Nano 30B A3B is a text model from NVIDIA, released on 14 December 2025. Both are served through api14 as chat models, and both accept text as input and return text as output, so at the level of basic request shape they are interchangeable.

The clearest split is in input handling and context. Muse Spark 1.3 Contributor accepts text, image, video and file inputs, while Nemotron 3 Nano 30B A3B accepts text only. Muse Spark 1.3 Contributor also carries a much larger context window, roughly four times that of Nemotron 3 Nano 30B A3B, which matters when you are feeding long documents, transcripts or multi file bundles into a single call. On price the two are not aligned in the same direction: Nemotron 3 Nano 30B A3B is the cheaper option for input tokens, while Muse Spark 1.3 Contributor is the cheaper option for output tokens. Neither model is listed as uniquely supporting tools, structured outputs or reasoning, so those capabilities are not a deciding factor between them.

For practical selection, start with the input you actually have. If your task involves screenshots, diagrams, video frames or uploaded files alongside text, Muse Spark 1.3 Contributor is the one that can take them; Nemotron 3 Nano 30B A3B cannot, so it would need a separate extraction step first. If your prompts are long, such as whole codebases, lengthy contracts or accumulated conversation history, the larger context window on Muse Spark 1.3 Contributor lets you avoid chunking and retrieval plumbing. If your workload is plain text, short to moderate in length, and generates a lot of output tokens, Nemotron 3 Nano 30B A3B is attractive because output is where Muse Spark 1.3 Contributor is not the cheaper side, and Nemotron 3 Nano 30B A3B also exposes a wider set of sampling controls including logit bias, logprobs, top logprobs, seed, stop and frequency and presence penalties, which helps when you need reproducible or tightly constrained generations.

Calling either model through api14 works the same way, because the API is OpenAI compatible. You point your client at the api14 base URL, send a chat completions request with your messages, and set the model field to the id you want. To switch between them you change only that string, between "meta/muse-spark-1.3-contributor" and "nvidia/nemotron-3-nano-30b-a3b". Your authentication, request structure and response parsing stay identical, so you can route between the two with a single configuration value or an environment variable rather than maintaining two client integrations.

There are still cases where Nemotron 3 Nano 30B A3B is the better pick even though Muse Spark 1.3 Contributor is the broader model. If your inputs are text only and your prompts fit comfortably inside a quarter million tokens, the extra modalities and the larger window on Muse Spark 1.3 Contributor buy you nothing, and you are paying the input side of the bill on the model that is not cheaper there. High volume text pipelines that emit long completions, or jobs that depend on logprobs, seeds or logit bias, are better served by Nemotron 3 Nano 30B A3B.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "meta/muse-spark-1.3-contributor" to "nvidia/nemotron-3-nano-30b-a3b" and prompts, streaming and tools keep working.

Meta: Muse Spark 1.3 Contributor details & playground →NVIDIA: Nemotron 3 Nano 30B A3B details & playground →

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": "nvidia/nemotron-3-nano-30b-a3b",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

Meta: Muse Spark 1.3 Contributor vs NVIDIA: Nemotron 3 Nano 30B A3B

Specifications

Key differences

In depth

Switch with one string

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