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Meta: Muse Glimmer 30B vs OpenAI: GPT-5.6 Luna

A side-by-side comparison of Meta: Muse Glimmer 30B ($1.05 / 1M tokens) and OpenAI: GPT-5.6 Luna ($0.70 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Meta: Muse Glimmer 30B	OpenAI: GPT-5.6 Luna
Provider	Meta	OpenAI
Input	$1.05 / 1M tokens	$0.70 / 1M tokens
Output	$4.20 / 1M tokens	$4.20 / 1M tokens
Cache read	$0.14 / 1M tokens	$0.07 / 1M tokens
Cache write	-	$0.88 / 1M tokens
Web search	-	$35.00 / 1K searches
Context window	131,072	1,050,000
Max output	16,384	128,000
Input	text, image	file, image, text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Aug 9, 2026	Jul 9, 2026

Key differences

OpenAI: GPT-5.6 Luna is 33% cheaper on input tokens.
OpenAI: GPT-5.6 Luna reads 8.0× more context (1,050,000 tokens).
A request with 1,000 input and 500 output tokens costs $0.00315 with Meta: Muse Glimmer 30B and $0.00280 with OpenAI: GPT-5.6 Luna.

In depth

Meta: Muse Glimmer 30B is a text model from Meta, listed under the model id meta/muse-glimmer-30b. OpenAI: GPT-5.6 Luna is a text model from OpenAI, listed under the model id openai/gpt-5.6-luna. Both are served through api14 as chat models you call from the same OpenAI-compatible endpoint, so the choice between them comes down to what your task actually needs rather than to any difference in how you integrate them.

The clearest split is context and input handling. GPT-5.6 Luna has the larger context window by a wide margin, and it accepts files as well as images and text on the input side, while Muse Glimmer 30B accepts text and images only. Both return text. On price, Luna is the cheaper of the two for input, and the two are about the same for output, so the cost difference shows up mainly when you are sending a lot of input tokens. Muse Glimmer 30B exposes a broader set of sampling and control parameters, including frequency and presence penalties, logit bias, min_p, repetition penalty, top_k, and seed, which gives you finer control over generation behavior if you tune those knobs. Luna's parameter list is narrower and includes verbosity and max_completion_tokens instead. Neither model is listed as uniquely supporting tools, structured outputs, or reasoning, so treat those as available on both rather than as a deciding factor.

For practical selection, reach for GPT-5.6 Luna when your input is large or file-based: long documents, whole repositories of text, PDFs or other files you want the model to read directly, or conversations where the accumulated context would otherwise force you to truncate. Its larger window and file input make it the natural default for retrieval-heavy or document-centric work, and its lower input price helps when you are feeding it a lot of tokens per call. Reach for Meta: Muse Glimmer 30B when your input is text or images and fits comfortably in its context window, and when you want tighter control over sampling through parameters like top_k, min_p, repetition penalty, or logit bias. It is also a reasonable pick when you want to pin behavior with a seed or shape output with penalties that Luna does not expose.

Calling either model through api14 works the same way. You send a request to the OpenAI-compatible chat completions endpoint with your api14 key, and the only thing that changes between the two is the model id: use meta/muse-glimmer-30b for Muse Glimmer 30B and openai/gpt-5.6-luna for GPT-5.6 Luna. Messages, roles, and the response shape stay the same, so you can swap models by changing that one string, or route between them per request based on input size or modality. Keep in mind that parameters are not identical across the two, so if you rely on top_k, min_p, logit_bias, or repetition penalty, those apply to Muse Glimmer 30B, while verbosity and max_completion_tokens apply to Luna.

There are still cases where Muse Glimmer 30B is the better pick even though Luna has the larger window and cheaper input. If your task is text or image based, fits within 131072 tokens, and benefits from fine-grained sampling control or reproducible seeds, Muse Glimmer 30B gives you options Luna does not, at about the same output price. Conversely, if you need to pass files directly or your context regularly exceeds what Muse Glimmer 30B can hold, Luna remains the better fit.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "meta/muse-glimmer-30b" to "openai/gpt-5.6-luna" and prompts, streaming and tools keep working.

Meta: Muse Glimmer 30B details & playground →OpenAI: GPT-5.6 Luna 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": "openai/gpt-5.6-luna",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

More comparisons

Muse Glimmer 30B vs GPT-5.6 Luna: API price, context & features · api14