Sunk Cost sunkcost.ai Data checked 2026-09-03

What hardware do you need to run Muse Glimmer 30B?

Muse Glimmer 30B at Q4_K_M is 17 GB of weights, with a context ceiling of 128k tokens. Meta's dense 30B under Apache 2.0, aimed at local agents. On the cheapest machine that runs it, a Framework Desktop, 32GB, it generates 11 tok/s at 32k of context, worked out from memory bandwidth.

Cheapest machine that runs itStrix Halo Framework Desktop, 32GB at $1,269
Fastest machine that runs itNVIDIA RTX PRO 6000 Blackwell, 96GB at $18,000card only — 81 tok/s estimated at 32k context
Honest answer on costPays back in 22 years at 500k tokens a day.

How good is Muse Glimmer 30B, really?

On the Artificial Analysis Intelligence Index v4.3 it scores 18 (high effort), which puts it in the Haiku-class band. In the same band as Anthropic's cheap, fast tier. Every current OpenAI model scores above this band. See the whole table.

Head to head with its neighbours on the leaderboard: vs Qwen3.6 35B-A3B above it, vs Gemma 4 26B-A4B below. One more model needs much the same memory at 32k of context: vs Qwen3.8 27B.

What Muse Glimmer 30B costs either way

Renting the same model costs $0.3 per million input tokens and $1.2 per million output (OpenRouter, cheapest active endpoint, checked 2026-10-29). Buying a machine only beats that if you use it hard enough, for long enough, that the hardware price divides down below the rental bill. What a million tokens costs each way puts the two prices side by side.

Machines that run Muse Glimmer 30B

Every machine here holds it to 128k, this model's own ceiling, so the choice between them is speed and price rather than how much you can keep in the window.

MachinePriceSpeed at 32kLongest contextPay-back
Strix Halo Framework Desktop, 32GB $1,269 11 tok/s estimated 128k Pays back in 22 years Run the numbers
Mac mini M6, 32GB $1,299 7.2 tok/s estimated 128k Pays back in 22 years Run the numbers
AMD Radeon AI PRO R9700, 32GB $1,299card only 31 tok/s estimated 128k Pays back in 22 years Run the numbers
NVIDIA GeForce RTX 5090, 32GB $1,999card only 69 tok/s estimated 128k Pays back in 33 years Run the numbers
MacBook Pro M5 (14-inch), 32GB $2,399 6.4 tok/s estimated 128k Pays back in 40 years Run the numbers
Mac Studio M5 Max, 36GB $2,499 19 tok/s estimated 128k Pays back in 41 years Run the numbers
DGX Spark GB10 Grace Blackwell, 128GB $4,699 11 tok/s estimated 128k Pays back in 81 years Run the numbers

The table is the cheapest machine in each family, not the only one that runs it: 44 of the 56 machines on this site hold it at 32k. Within a family only memory decides, so that is every Mac Studio and Strix Halo box at any size, every NVIDIA card with 24GB or more, every Mac mini and MacBook Pro with 32GB or more, the Radeon AI PRO R9700, 32GB and the DGX Spark, 128GB. One table sets every machine against the others: price, the memory its GPU can use, what it holds and how long it takes to pay for itself.

One machine per family, cheapest first. Speeds are measured where a public benchmark exists and estimated from memory bandwidth otherwise; the calculator says which for any configuration. The longest context is the longest setting the calculator offers that the machine still holds this model at, cache included, and no machine is shown taking it past its own 128k limit. Each one opens the calculator on that machine at that length.

For scale, the calculator starts from 80 tok/s for a hosted API and times a local machine against it. Nothing above reaches it, and the quickest is 69 tok/s.

The cheapest machine that runs it is sold with 32 GB. There is a page on what 32 GB runs, machine by machine: it names the 6 machines here sold at that size, and the 32 current models the roomiest of them holds at 32k, this one among them.

It fits in less memory than that: the smallest size here that runs it at 32k is 24 GB, on the GeForce RTX 3090, 24GB at $1,499, card only, which hands a model 23 GB and is no longer sold.

Run Muse Glimmer 30B at 128k on the Strix Halo Framework Desktop, 32GB

How much memory does Muse Glimmer 30B need at 128k?

Every figure above is priced at 32k of context. At 128k, this model's own ceiling, Muse Glimmer 30B needs 19.1 GB rather than 17.8 GB. The weights are the same either way; the key-value cache goes from 0.5 GB to 1.8 GB.

The window costs nothing in hardware: the same 30 of the 37 machines here still sold at a published price hold Muse Glimmer 30B at both lengths, and the cheapest of them is the Framework Desktop, 32GB at $1,269.

On the Framework Desktop, 32GB it runs 11 tok/s estimated at 32k and 10 tok/s estimated at 128k. Every token generated reads the whole cache back, so a longer window is slower as well as bigger.

The specifics

Parameters
29.8B
Quantisation
Q4_K_M
Weights on disk
17 GB
KV cache
0.5 GB at 32k context — 3 sliding-window layers (2048) per full-attention layer, so the cache barely grows with context. Multimodal: the vision projector is a separate ~1.4 GB file, not counted here. How weights and cache add up.
Maximum context
128k tokens
Licence
Apache 2.0
Sources
meta-models/Muse-Glimmer-30B, bartowski/Muse-Glimmer-30B-GGUF