muse-glimmer-30b
Fireworks AI/🇺🇸 US/chat
Muse Glimmer 30B is a dense causal language model distilled from Muse Spark and purpose-built for autonomous agentic work. It combines multi-step reasoning, reliable schema-based tool calling, and failure recovery with multimodal understanding via a ~1.8B ViT-G/14 perception encoder, supporting interleaved text and image input, a 131K+ context window, and selectable reasoning strength (low through xhigh). Trained on data from over 100 languages, Muse Glimmer performs strongly for its size class on agentic benchmarks including MCP Atlas, DeepSearch QA, Gaia2 and SWE-Bench Pro, and is released under Apache 2.0.MoreLess
Which id to call
fireworks/muse-glimmer-30bThis exact deployment on Fireworks AI, with no routing and no failover. Send it as the model field.
Input /1M
$0.35
$0.04 cached
Output /1M
$1.50
4.3x input
Context
131K
131K output
Added
Aug 2026
chat
Capabilities 5/8
Provider rates
What muse-glimmer-30b costs
Provider prices per 1M tokens, updated October 2, 2026.moreless
These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.
Input /1M
$0.35
Output /1M
$1.50
Cache write /1M
-
Cache read /1M
$0.04
What a workload costs
- 100K input + 10K output
- $0.0500
- 1M input + 100K output
- $0.50
- 10M input + 1M output
- $5.00
At the rates above, before caching. A cache read costs $0.04 per 1M, so repeated context lands under these figures.
model=
Which id to call
One base url, https://router.requesty.ai/v1, and one key for every id here.
fireworks/muse-glimmer-30bThis exact deployment on Fireworks AI, with no routing and no failover. Send it as the model field.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="fireworks/muse-glimmer-30b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Reference
Specs and data terms
What the catalog reports for this deployment, and what the provider does with the traffic.
Public leaderboards
Benchmark scores
Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.
No benchmarks are published for this exact variant yet.
Region-specific deployments and highspeed tiers usually share scores with their base model. Try the base model page or the Fireworks AI models overview.
Same provider
More from Fireworks AI
Newest first, on the same provider and the same key.
Reference
muse-glimmer-30b questions
How much does muse-glimmer-30b cost?
muse-glimmer-30b is priced at $0.35 per million input tokens and $1.50 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
What is the context window of muse-glimmer-30b?
muse-glimmer-30b has a context window of 131K tokens, with a maximum output of 131K tokens per response. That's roughly 175 words of input you can fit in a single prompt.
What can muse-glimmer-30b do?
muse-glimmer-30b supports vision input, tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use muse-glimmer-30b with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "fireworks/muse-glimmer-30b". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run muse-glimmer-30b through Requesty?
Yes. muse-glimmer-30b runs through Requesty's OpenAI-compatible API, served from Fireworks AI. You do not host the model yourself: point base_url at Requesty, set the model to "fireworks/muse-glimmer-30b", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call muse-glimmer-30b through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.