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

Qwen3.6 27B vs Arete-27B

Qwen3.6 27B scores 22 on the intelligence index, and Arete-27B has not been placed on it. Both take the same machine to start: the cheapest here that runs either is the Framework Desktop, 32GB, at $1,269. On it, they run at much the same speed: 10 and 9.9 tok/s, both estimated from memory bandwidth. At 500k tokens a day the Framework Desktop, 32GB pays for itself in 22 years running Qwen3.6 27B, against 92 years running Arete-27B.

Qwen3.6 27BArete-27B
Intelligence index22not placed
ClassHaiku-classnot yet placed
Weights17 GB17 GB
Needs at 32k19 GB19 GB
QuantisationQ4_K_MQ4_K_M
Parameters27.8B27.4B
Max context256k256k
API price per 1M$0.25 in / $2 out$0.039 in / $1.25 outpriced as Qwen3.8 27B
LicenceApache 2.0Apache 2.0
Machines here that run it30 of 3730 of 37
Cheapest machine that runs itStrix Halo Framework Desktop, 32GB $1,269Strix Halo Framework Desktop, 32GB $1,269

Run Qwen3.6 27B on the Framework Desktop, 32GB · or Arete-27B

Jump to: Side by side on the Framework Desktop, 32GB · 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, 32GB

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, 32GB, at $1,269.

Qwen3.6 27BArete-27B
Speed at 32k10 tok/s estimated9.9 tok/s estimated
Pay-back on this machinePays back in 22 yearsPays back in 92 years
API cost per month$5.47$1.75priced as Qwen3.8 27B

Run Qwen3.6 27B on the Framework Desktop, 32GB · or Arete-27B

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, 32GB. Qwen3.6 27B 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 useQwen3.6 27BArete-27B
50ka few chats a day217 years925 years
200klight assistant use54 years231 years
1Ma moderate coding-assistant day11 years46 years
4Mheavy coding with an agent2.7 years12 years
20Magents running most of the day9.3 monthsits ceiling3.4 yearsits ceiling

The Framework Desktop, 32GB cannot generate 20M tokens a day on either model: at most 14M on Qwen3.6 27B and 13.7M on Arete-27B. Both figures on that row are for the most it can do.

Run Qwen3.6 27B at 20M tokens a day · or Arete-27B

Memory is not what separates them

Qwen3.6 27B needs 19 GB of memory at 32k of context and Arete-27B needs 19 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.

Qwen3.6 27B is also head to head with MiniMax M2.7 above it on the leaderboard and Nemotron 3.5 Bolt 74B-A9B below it. Arete-27B is also head to head with Qwen3.8 27B and Gemma 3 27B it, which need much the same memory.

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 Qwen3.6 27B · every machine that runs Arete-27B · every other match-up · both against the frontier · the quickest pay-back at each level of use