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Muse Spark 1.3 Contributor vs Reka Flash 3: API price, context & features · api14

Meta: Muse Spark 1.3 Contributor vs Reka Flash 3

A side-by-side comparison of Meta: Muse Spark 1.3 Contributor ($0.35 / 1M tokens) and Reka Flash 3 ($0.35 / 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	Reka Flash 3
Provider	Meta	Reka AI
Input	$0.35 / 1M tokens	$0.35 / 1M tokens
Output	$0.70 / 1M tokens	$0.70 / 1M tokens
Cache read	$0.00700 / 1M tokens	-
Web search	$8.75 / 1K searches	-
Context window	1,048,576	65,536
Max output	943,718	58,982
Input	text, image, video, file	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Sep 2, 2026	Mar 12, 2025

Key differences

Both have about the same input price.
Meta: Muse Spark 1.3 Contributor reads 16.0× more context (1,048,576 tokens).
Only Meta: Muse Spark 1.3 Contributor supports tool calling.
A request with 1,000 input and 500 output tokens costs $0.000700 with Meta: Muse Spark 1.3 Contributor and $0.000700 with Reka Flash 3.

In depth

Meta: Muse Spark 1.3 Contributor is a text model from Meta, released on 2 September 2026. Reka Flash 3 is a text model from Reka AI, released on 12 March 2025. Both are served through api14 as chat models with text output, so at the level of basic generation they occupy the same slot in your stack. The differences show up in what you can feed them, how much you can feed them at once, and which request parameters they accept.

The clearest split is context and input handling. Muse Spark 1.3 Contributor accepts a context window of 1,048,576 tokens, while Reka Flash 3 accepts 65,536 tokens, so the Meta model gives you a much larger working set for long documents or extended conversations. Muse Spark 1.3 Contributor also takes text, image, video and file inputs, whereas Reka Flash 3 takes text only. On tool calling the two are not equivalent either: Muse Spark 1.3 Contributor supports tools and tool_choice, and Reka Flash 3 does not list them. Both expose structured outputs, reasoning and include_reasoning, so structured generation and reasoning traces are available on either side. The parameter lists diverge elsewhere: Reka Flash 3 supports frequency_penalty, presence_penalty, logprobs, top_logprobs, seed and stop, which Muse Spark 1.3 Contributor does not list, while Muse Spark 1.3 Contributor supports repetition_penalty, reasoning_effort and response_format, which Reka Flash 3 does not list. On price the two are about the same for both input and output, so cost is not the deciding factor here.

For most new work, reach for Muse Spark 1.3 Contributor first. If your task involves long source material such as a full repository, a lengthy contract or a multi hour transcript, the larger context window removes the need to chunk and stitch. If your input includes screenshots, diagrams, video frames or attached files, it is the only one of the two that accepts them. If your application is agentic and depends on tool calls, or you want to steer reasoning depth with reasoning_effort, it is again the only option. Reka Flash 3 remains a reasonable choice when your input is plain text, your prompt fits comfortably inside 65,536 tokens, and you want sampling controls that Muse Spark 1.3 Contributor does not expose, such as seed for reproducible runs, logprobs and top_logprobs for inspecting token level confidence, or frequency_penalty and presence_penalty for tuning repetition. Those are practical reasons to pick it for evaluation harnesses, classification with confidence readouts, and short text transformations.

Calling either model through api14 works the same way, because the endpoint is OpenAI compatible. You point your existing OpenAI client at the api14 base URL, send your key, and set the model field. Switching between the two is a single string change: use meta/muse-spark-1.3-contributor or rekaai/reka-flash-3. The request body shape, the messages array and the response parsing stay identical, so you can keep one code path and swap the id per request or per environment. The one thing to watch is parameters: if you send seed or logprobs to Muse Spark 1.3 Contributor, or tools or reasoning_effort to Reka Flash 3, the call will not behave as it does on the other model, so gate those fields on the model id you are sending.

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 "rekaai/reka-flash-3" and prompts, streaming and tools keep working.

Meta: Muse Spark 1.3 Contributor details & playground →Reka Flash 3 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": "rekaai/reka-flash-3",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

Meta: Muse Spark 1.3 Contributor vs Reka Flash 3

Specifications

Key differences

In depth

Switch with one string

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