Meta Llama: Muse Glimmer 30B
meta/muse-glimmer-30b
Access Muse Glimmer 30B from Meta Llama using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "meta/muse-glimmer-30b"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "meta/muse-glimmer-30b"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="meta/muse-glimmer-30b",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "meta/muse-glimmer-30b",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Muse Glimmer 30B is a 30-billion-parameter dense model from Meta Superintelligence Labs, pairing a causal transformer with a 1.8-billion-parameter vision encoder for text and image input. It's released under an Apache 2.0 license, Meta's first fully open-weight model since Muse Spark moved to a paid API.
On Meta's own benchmarks, it scores 76.0 on SWE-Bench Verified, 51.2 on SWE-Bench Pro, 94.7 on AIME 2026, 83.5 on GPQA Diamond, 75.5 on MCP Atlas, and 74.6 on DeepSearch QA, ahead of similarly sized open models like Gemma4 31B and Qwen3.6 27B on Meta's reporting. These figures are vendor-reported and not independently verified.
Where Muse Spark targets large-scale multi-agent orchestration, Muse Glimmer sits a size tier down, aimed at tool use, multi-step reasoning, coding, and LLM-as-a-judge evaluation with a 131,072-token context window. It fits developers who want agentic and coding capability at lower cost than the larger Muse Spark models.
Context Window 131K
tokens
Max Output 131K
tokens
Input Cost $0.35
per million tokens
Output Cost $1.5
per million tokens
Input text, image
modalities
Tool Use Yes
Release Date Aug 9, 2026
Model Playground
Try Muse Glimmer 30B instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Meta Llama
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Muse Spark 1.2
Muse Spark 1.2 is Meta Superintelligence Labs' coding-focused update to Muse Spark 1.1, released alongside Muse Code, a terminal coding agent it powers. Meta scaled up training compute on coding tasks and training-environment diversity, aiming at code generation, debugging, codebase understanding, and long-horizon work like whole-repository generation. On Meta's own evaluation harness, Muse Spark 1.2 scored 82.9% on Terminal-Bench 2.1 and 59.3% on DeepSWE 1.1, edging OpenAI's GPT-5.6 Terra (81.8%) and xAI's Grok 4.5 (81.6%) on Terminal-Bench but trailing Anthropic's Opus 5 (86.7%). These are vendor-run numbers, not yet independently verified on the public leaderboards. It keeps the 1,048,576-token context window and text, image, video, audio, and PDF input from 1.1, at the same $1.25 per million input and $4.25 per million output token pricing. A separate contributor tier offers lower rates in exchange for letting Meta train on your prompts and completions.
ChatMuse Spark 1.1
Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs, built for agentic workflows. It accepts text, images, video, audio, and PDF documents as input and returns text, with a 1,048,576-token context window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates tasks or as a subagent, and it generalizes zero-shot to new tools, MCP servers, and custom skills. It supports parallel function calling, structured output, built-in search with citations, and configurable reasoning effort, and Meta reports strong results on coding across large codebases, computer-use tasks, and visual-to-code generation. This is Meta's first model available through a paid API, priced at $1.25 per million input tokens and $4.25 per million output tokens, aimed at developers building agentic coding tools and enterprise workflow automation.
ChatLlama 4 Maverick
Llama 4 Maverick is Meta's 400 billion total parameter MoE model with 17B active parameters and 128 experts, supporting 1M token context. It's natively multimodal with state-of-the-art performance on coding, reasoning, and image understanding tasks.
Frequently Asked Questions
You can access Muse Glimmer 30B by Meta Llama through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Muse Glimmer 30B to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.35 |
| Output | $1.5 |
Muse Glimmer 30B was created by Meta Llama and released on Aug 9, 2026.
Muse Glimmer 30B supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Muse Glimmer 30B can generate up to 131K tokens in a single response.
Muse Glimmer 30B accepts the following input types: text, image. It produces: text.
Yes, Muse Glimmer 30B supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Muse Glimmer 30B API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Muse Glimmer 30B to your app without worrying about API keys or setup.
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