Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...
Context
131Ktokens
About 187 pages of text at once
Max output
16Ktokens
About 23 pages in one answer
Intelligence
6.3/ 100
Above 5% of the catalogue
Output speed
81tokens/s
A 500-word answer in about 8.6 s
From public market statistics for this model
First token
0.8s
Reasoning models start later
From public market statistics for this model
Health, 30 days
98.08%
20 of 30 days without a fault
IranRouter’s measurements
Price & cost
Every rate in Rial. A request pays only for the tokens it actually uses.
| Input | 824,409 | IRR / 1M tokens |
|---|---|---|
| Output | 3,297,638 | IRR / 1M tokens |
| Reasoning tokensThe output rate | 3,297,638 | IRR / 1M tokens |
| Cache read | 109,921 | IRR / 1M tokens |
| Image input tokensThe input rate | 824,409 | IRR / 1M tokens |
With prompt caching, the fixed part of your prompt is billed at the cache-read rate on later requests.
What would this model cost you a month?
Monthly cost
133.55MIRR
4.45M IRR a day, 2,226 IRR each request
The same work on peer models
30 days at today’s rate.
Rial price over 90 days
It moves with the exchange rate; the steps are the maker’s own price changes. Built at today’s margin, so approximate if the margin changed in the window.
Performance, 30 days
Health is measured by IranRouter itself: a day counts as healthy unless requests to this model failed on our side or it could not be served. First token and speed come from IranRouter’s traffic, and from public market statistics for this model on days without enough of it.
Daily health98.08%
Time to first token0.94 s
Output speed83 tokens/s
Place in the market
By usage across the global model market.
This model isn’t ranked yet.
Among its peers
Cost of one message against intelligence; this model is highlighted.
Cost of one message, IRR (log scale)
Capabilities
- Input
- TextImage
- Output
- Text
Parameters it accepts
frequency_penaltyinclude_reasoninglogit_biasmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_pOther benchmarks
Design contests
- UI componentsElo: 1,210Win rate: 41%
- WebsitesElo: 1,162Win rate: 36%
- Code (overall)Elo: 1,147Win rate: 34%
- Game devElo: 1,107Win rate: 30%
Standard tests
- GPQA DiamondScore: 81%Tasks: 1,584
- τ-bench Verified AirlineScore: 75%Tasks: 350
Start in a minute
The official OpenAI and Anthropic SDKs; only the address and the key change.
# pip install openai from openai import OpenAI client = OpenAI( base_url="https://iranrouter.com/v1", api_key="ir-...", ) r = client.chat.completions.create( model="meta/muse-glimmer-30b", messages=[{"role": "user", "content": "Hello, introduce yourself"}], ) print(r.choices[0].message.content)
Peer models
Its family and models with a close score; the last column compares one message’s cost with this model.
| Model | Against this model | ||||
|---|---|---|---|---|---|
| NVIDIA: Nemotron 3.5 LightningNVIDIA | 658 | 5.5 | 108 | 262K | 80% cheaper |
| Google: Gemini 3.5 Flash LiteGoogle | 5,069 | 11.7 | 132 | 1M | 54% dearer |
| NVIDIA: Nemotron 3 UltraNVIDIA | 6,576 | 11.8 | 69 | 262K | 100% dearer |
Technical specs
- ID
meta/muse-glimmer-30b- Maker
- Meta
- Tokenizer
- Other
- Released
- Aug 9, 2026
- Added to IranRouter
- Aug 19, 2026
- Context
- 131,072 tokens
- Max output
- 16,384 tokens
- Weights
- meta-models/Muse-Glimmer-30B
Default parameters
top_k=64top_p=0.95temperature=1Scores by Artificial Analysis, Design Arena, as of Oct 31, 2026