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

What can you run with 128 GB of memory?

A model does not get the 128 GB. On the Framework Desktop, 128GB it gets 96 GB and on the DGX Spark, 128GB it gets 119.5 GB, because the system keeps a share of it, and how much differs by machine. That is 33 of the 39 current models at 32k of context either way, and the strongest of them is Qwen3.8 27B.

What a model gets96 GB to 119.5 GB of the 128 GB, depending on the machine. Each machine's page says where the rest goes.
Models that fit at 32k33 of the 39 current ones, at the quantisation this site lists each at.
The strongest of themQwen3.8 27B, sonnet-class.
Cheapest machine at this sizeStrix Halo Framework Desktop, 128GB at $3,449.

Run the numbers on Qwen3.8 27B at 128 GB

Jump to: The machines sold with 128 GB · Models that fit in 128 GB · What 192 GB adds over 128 GB · How much context 128 GB leaves room for · Does a 128 GB machine pay for itself?

The machines sold with 128 GB

There are 11 machines here with 128 GB, and what they hand a model is not the same figure. The fourth column is what each one holds at 32k of context, and it is the number that machine's own page prints.

MachineWhat a model getsPriceModels it holds at 32kStrongest of them
DGX Spark, 128GB 119.5 GB $4,699 33 Qwen3.8 27B Run the numbers
Framework Desktop, 128GB 96 GB $3,449 33 Qwen3.8 27B Run the numbers
Mac Studio M4 Max, 128GBprevious 96 GB $3,499 33 Qwen3.8 27B Run the numbers
GMKtec EVO-X2, 128GB 96 GB $3,500 33 Qwen3.8 27B Run the numbers
GMKtec EVO-X3, 128GB 96 GB $3,600 33 Qwen3.8 27B Run the numbers
Minisforum MS-S1 Max, 128GB 96 GB $3,799 33 Qwen3.8 27B Run the numbers
Beelink GTR9 Pro, 128GB 96 GB $4,349 33 Qwen3.8 27B Run the numbers
Corsair AI Workstation 300, 128GB 96 GB $4,700 33 Qwen3.8 27B Run the numbers
Mac Studio M5 Max, 128GB 96 GB $5,099 33 Qwen3.8 27B Run the numbers
HP Z2 Mini G1a, 128GB 96 GB $5,544 33 Qwen3.8 27B Run the numbers
MacBook Pro M5 Max (16-inch), 128GB 96 GB $6,999 33 Qwen3.8 27B Run the numbers

List prices, and the memory each maker publishes. A machine marked previous is one that is no longer sold, priced at what it launched at.

Models that fit in 128 GB

Every current model the roomiest 128 GB machine here holds at 32k of context, strongest first. The third column is the whole job at once: the weights plus the cache for 32k of context. The fourth says how many of the machines at this size have room for it, which is the part a size on its own cannot tell you. Speeds are on the DGX Spark, 128GB, the machine this list is cut from; speed follows memory bandwidth rather than memory size, so another machine at 128 GB runs the same model at its own rate, and its page gives every one of them.

ModelParametersNeeds at 32kMachines at 128 GBSpeed on the DGX Spark, 128GB
Qwen3.8 27BQ4_K_M 27.8B 18.6 GB 11 of 11 11 tok/s estimated Run the numbers
Ling 3.0 flashQ4_K_M 124B 81.6 GB 11 of 11 26 tok/s estimated Run the numbers
Qwen3.6 27BQ4_K_M 27.8B 19 GB 11 of 11 11 tok/s estimated Run the numbers
Qwen3.6 35B-A3BQ4_K_M 36B 22.8 GB 11 of 11 70 tok/s estimated Run the numbers
Muse Glimmer 30BQ4_K_M 29.8B 17.8 GB 11 of 11 11 tok/s estimated Run the numbers
Gemma 4 26B-A4BQ4_K_M 25.2B 17.8 GB 11 of 11 52 tok/s estimated Run the numbers
Qwen3.5 122B-A10BUD-Q4_K_M 125.1B 79.1 GB 11 of 11 25 tok/s estimated Run the numbers
Granite 4.2 30BQ4_K_M 29.3B 26.3 GB 11 of 11 7.8 tok/s estimated Run the numbers
Gemma 4 31B itQ4_K_M 31.3B 25.8 GB 11 of 11 7.9 tok/s estimated Run the numbers
GLM-4.7-FlashQ4_K_M 31.2B 20.1 GB 11 of 11 50 tok/s estimated Run the numbers
Nemotron 3.5 Lightning 30B-A3BQ4_K_M 31.6B 25.7 GB 11 of 11 68 tok/s estimated Run the numbers
Gemma 4 12BQ4_K_M 12B 8 GB 11 of 11 26 tok/s estimated Run the numbers
Qwen3.5 9BQ4_K_M 9.7B 6.8 GB 11 of 11 30 tok/s estimated Run the numbers
Qwen3.5 4BQ4_K_M 4.7B 3.8 GB 11 of 11 54 tok/s estimated Run the numbers
MiniCPM5 2BQ4_K_M 2.5B 3 GB 11 of 11 69 tok/s estimated Run the numbers
gpt-oss-120bMXFP4 116.8B 64.6 GB 11 of 11 41 tok/s measured Run the numbers
Granite 4.2 8BQ4_K_M 8B 10.7 GB 11 of 11 19 tok/s estimated Run the numbers
Ling 3.0 tinyQ4_K_M 7.9B 6.4 GB 11 of 11 74 tok/s estimated Run the numbers
Mistral Small 4 (119B-2603)Q4_K_M 119.4B 74.5 GB 11 of 11 40 tok/s estimated Run the numbers
Qwen3-Coder NextQ4_K_M 79.7B 49.2 GB 11 of 11 68 tok/s estimated Run the numbers
Qwen3-Coder 30B-A3BQ4_K_M 30.5B 21.8 GB 11 of 11 34 tok/s measured Run the numbers
Devstral 2 123BQ4_K_M 125B 86.7 GB 11 of 11 2.4 tok/s estimated Run the numbers
gpt-oss-20bMXFP4 20.9B 12.9 GB 11 of 11 60 tok/s measured Run the numbers
Gemma 4 E4BQAT Q4_0 8B 5.7 GB 11 of 11 51 tok/s estimated Run the numbers
Devstral Small 2 24BQ4_K_M 24B 19.7 GB 11 of 11 10 tok/s estimated Run the numbers
LFM2.5 2.6BQ4_K_M 2.7B 2.2 GB 11 of 11 93 tok/s estimated Run the numbers
Ministral 3 14BQ4_K_M 14B 13.6 GB 11 of 11 15 tok/s estimated Run the numbers
Ministral 3 8BQ4_K_M 8.9B 9.8 GB 11 of 11 21 tok/s estimated Run the numbers
Ornith 1.5 35B-A3BQ4_K_M 36B 22.4 GB 11 of 11 71 tok/s estimated Run the numbers
KAT-Coder V2.5 Dev 35B-A3BQ4_K_M 34.7B 22.1 GB 11 of 11 70 tok/s estimated Run the numbers
Laguna XS 2.1Q4_K_M 33.4B 21.7 GB 11 of 11 55 tok/s estimated Run the numbers
Ornith 1.5 9BQ4_K_M 9.7B 6.9 GB 11 of 11 30 tok/s estimated Run the numbers
Spark-X2.5 4BQ4_K_M 4.1B 3.9 GB 11 of 11 53 tok/s estimated Run the numbers

For scale, the calculator starts from 80 tok/s for a hosted API and times a local machine against it. 1 of the 33 above reaches it, and the slowest is 2.4 tok/s.

Superseded models are left out of the count, because what a machine is worth buying for is what you would run on it today; the leaderboard ranks every model this site lists, older ones included. Where the cache figure comes from is one section of the memory guide.

What 192 GB adds over 128 GB

The machine here with 192 GB that hands a model the most of it is the Framework Desktop, 192GB, at 160 GB, and it holds 36 of the 39. At 128 GB the most is 119.5 GB, on the DGX Spark, 128GB, holding 33. The step adds Qwen3.8 Flash Next, DeepSeek V4-Flash and MiniMax M2.7. The strongest goes from Qwen3.8 27B to Qwen3.8 Flash Next.

Both sides are read off the machine at each size that hands a model the most, so the comparison is the best case against the best case. The table above has every machine at 128 GB and what each of them holds.

How much context 128 GB leaves room for

The cache grows with the window you ask for, so the same machine holds fewer models the longer the context. One column here for each amount a 128 GB machine hands over. A model is counted only where its own context ceiling reaches that far.

Context96 GB to a modelFramework Desktop, 128GB119.5 GB to a modelDGX Spark, 128GB
4k 3333
8k 3333
16k 3333
32k default 3333
64k 3233
128k 3232

Counted over the 39 current models, at the quantisation each is listed at and with the cache at 16 bits. The calculator has a switch for a smaller cache, which changes both what fits and how fast a long window runs.

Does a 128 GB machine pay for itself?

On the Strix Halo Framework Desktop, 128GB at $3,449, the cheapest machine at 128 GB with a published price, the model that pays it back soonest at 500k tokens a day is Qwen3.8 27B, in 45 years. At 20M tokens a day, agents running most of the day, it is Qwen3.5 122B-A10B in 16 months.

The sum is the same everywhere on this site: what the same work costs to rent, less what the electricity costs to generate it, against the price of the machine. The best buys rank the quickest pay-back at every level of use, and what it costs a month puts the machine and the API bill in the same shape.

Put your own usage in

Every figure is at 32k of context unless the row says otherwise, with the cache at 16 bits and each model at the quantisation this site lists it at. Weights are the published file sizes on each model's page, and the cache is worked out from the architecture recorded there. What a model gets is the memory the GPU can address, which each machine's page explains. Speeds say whether anybody measured them; where they were not, they are worked out from memory bandwidth. To change the context, the quantisation or the price you would pay, open the calculator. For the sizes either side of this one, the memory guide has the ladder in full.