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

Qwen3.6 35B-A3B vs Gemma 4 31B it

Qwen3.6 35B-A3B scores higher on the intelligence index, 19 against 15. Both take the same machine to start: the cheapest here that runs either is the Framework Desktop, 32GB, at $1,269. On it, Qwen3.6 35B-A3B is about 6.7× quicker: 56 tok/s against 8.3, both estimated from memory bandwidth. At 500k tokens a day the Framework Desktop, 32GB pays for itself in 83 years running Qwen3.6 35B-A3B, against 119 years running Gemma 4 31B it.

Qwen3.6 35B-A3BGemma 4 31B it
Intelligence index1915
ClassHaiku-classHaiku-class
Weights22 GB20 GB
Needs at 32k23 GB23 GB
QuantisationQ4_K_MQ4_K_M
Parameters36B (3B active)31.3B
Max context256k256k
API price per 1M$0.05 in / $0.7 out$0.09 in / $0.34 out
LicenceApache 2.0Apache 2.0
Machines here that run it28 of 3728 of 37
Cheapest machine that runs itStrix Halo Framework Desktop, 32GB $1,269Strix Halo Framework Desktop, 32GB $1,269

Run Qwen3.6 35B-A3B on the Framework Desktop, 32GB · or Gemma 4 31B it

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 35B-A3BGemma 4 31B it
Speed at 32k56 tok/s estimated8.3 tok/s estimated
Pay-back on this machinePays back in 83 yearsPays back in 119 years
API cost per month$1.38$1.61

Run Qwen3.6 35B-A3B on the Framework Desktop, 32GB · or Gemma 4 31B it

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 35B-A3B 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 35B-A3BGemma 4 31B it
50ka few chats a day831 years1,191 years
200klight assistant use208 years298 years
1Ma moderate coding-assistant day42 years60 years
4Mheavy coding with an agent10 years15 years
20Magents running most of the day2.1 years5.2 yearsits ceiling

The Framework Desktop, 32GB generates at most 11.5M tokens a day on Gemma 4 31B it, 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 Qwen3.6 35B-A3B at 20M tokens a day · or Gemma 4 31B it

Memory is not what separates them

Qwen3.6 35B-A3B needs 23 GB of memory at 32k of context and Gemma 4 31B it needs 23 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 35B-A3B is also head to head with Qwen3.6 27B above it on the leaderboard and Muse Glimmer 30B below it. Gemma 4 31B it is also head to head with Qwen3.5 122B-A10B above it on the leaderboard, Granite 4.2 30B below it and Gemma 3 27B it, the last-generation Gemma nearest it in size. Two more models need much the same memory: Qwen3 30B-A3B Instruct 2507 and Qwen3-Coder 30B-A3B.

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 35B-A3B · every machine that runs Gemma 4 31B it · every other match-up · both against the frontier · the quickest pay-back at each level of use