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

GLM-4.5-Air vs Mistral Small 4 (119B-2603)

GLM-4.5-Air and Mistral Small 4 (119B-2603) both score 11 on the intelligence index. Both take the same machine to start: the cheapest here that runs either is the Framework Desktop, 128GB, at $3,449. On it, Mistral Small 4 (119B-2603) is about 3.2× quicker: 32 tok/s against 10, both estimated from memory bandwidth. At 500k tokens a day the Framework Desktop, 128GB pays for itself in 114 years running Mistral Small 4 (119B-2603), against 139 years running GLM-4.5-Air.

GLM-4.5-AirMistral Small 4 (119B-2603)
Intelligence index1111
ClassBelow every hosted tierBelow every hosted tier
Weights73 GB74 GB
Needs at 32k79 GB75 GB
QuantisationQ4_K_MQ4_K_M
Parameters110.5B (12B active)119.4B (6B active)
Max context128k1M
API price per 1M$0.13 in / $0.85 out$0.15 in / $0.6 out
LicenceMITApache 2.0
Machines here that run it12 of 3712 of 37
Cheapest machine that runs itStrix Halo Framework Desktop, 128GB $3,449Strix Halo Framework Desktop, 128GB $3,449

Run GLM-4.5-Air on the Framework Desktop, 128GB · or Mistral Small 4 (119B-2603)

Jump to: Side by side on the Framework Desktop, 128GB · How much use it takes to pay for the machine · Memory is not what separates them · The assumptions behind both columns

Side by side on the Framework Desktop, 128GB

The cheapest machine that runs either model is the same one, so this is the pair doing the same work on the same hardware: Strix Halo Framework Desktop, 128GB, at $3,449.

GLM-4.5-AirMistral Small 4 (119B-2603)
Speed at 32k10 tok/s estimated32 tok/s estimated
Pay-back on this machinePays back in 139 yearsPays back in 114 years
API cost per month$2.66$2.71

Run GLM-4.5-Air on the Framework Desktop, 128GB · or Mistral Small 4 (119B-2603)

How much use it takes to pay for the machine

Everything above is at 500k tokens a day. Pay-back moves with how much you actually run, so here are both models at the five levels of use the calculator names, on the Framework Desktop, 128GB. Mistral Small 4 (119B-2603) pays for it sooner at every level of use, so which of them to run does not turn on how hard you work it.

A day's useGLM-4.5-AirMistral Small 4 (119B-2603)
50ka few chats a day1,392 years1,140 years
200klight assistant use348 years285 years
1Ma moderate coding-assistant day70 years57 years
4Mheavy coding with an agent17 years14 years
20Magents running most of the day5.0 yearsits ceiling2.8 years

The Framework Desktop, 128GB generates at most 13.8M tokens a day on GLM-4.5-Air, so that column's figure at 20M tokens a day is for the most it can do, not for the whole of what was asked.

Run GLM-4.5-Air at 20M tokens a day · or Mistral Small 4 (119B-2603)

Memory is not what separates them

GLM-4.5-Air needs 79 GB of memory at 32k of context and Mistral Small 4 (119B-2603) needs 75 GB. Every machine priced here that runs one runs the other, at 32k of context. So the choice between them is what each is good at, how fast it runs and what the same work costs on an API, not what you have to buy to hold it.

GLM-4.5-Air is also head to head with Granite 4.2 8B above it on the leaderboard. Two more models need much the same memory: Qwen3.5 122B-A10B and Devstral 2 123B. Mistral Small 4 (119B-2603) is also head to head with Qwen3 30B-A3B Instruct 2507 below it on the leaderboard. One more model needs much the same memory: Ling 3.0 flash.

The assumptions behind both columns

Both columns use the same usage: 500k tokens a day at 15:1 input to output, 32k of context, $0.17 per kWh, and today's API prices held flat. Speeds marked estimated are worked out from memory bandwidth rather than measured, and pay-back scales with them. Where nobody rents an open model by the token, its API prices are the nearest hosted model's, named beside them. Machines are the 37 here with a published price that are still sold. Change any of it in the calculator.

More head to head: every machine that runs GLM-4.5-Air · every machine that runs Mistral Small 4 (119B-2603) · every other match-up · both against the frontier · the quickest pay-back at each level of use