Qwen3.5 122B-A10B vs Mistral Small 4 (119B-2603)

Qwen3.5 122B-A10B scores higher on the intelligence index, 16 against 11. 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 1.6× quicker: 32 tok/s against 20, both estimated from memory bandwidth. At 500k tokens a day the Framework Desktop, 128GB pays for itself in 53 years running Qwen3.5 122B-A10B, against 114 years running Mistral Small 4 (119B-2603).

Run Qwen3.5 122B-A10B on the Framework Desktop, 128GB · or Mistral Small 4 (119B-2603)

Ratings are coarse on purpose: they say what a model is usable for, not where it places to the decimal.

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.

Run Qwen3.5 122B-A10B 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. Qwen3.5 122B-A10B pays for it sooner at every level of use, so which of them to run does not turn on how hard you work it.

Run Qwen3.5 122B-A10B at 20M tokens a day · or Mistral Small 4 (119B-2603)

Memory is not what separates them

Qwen3.5 122B-A10B 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.

Qwen3.5 122B-A10B is also head to head with Gemma 4 26B-A4B above it on the leaderboard and Gemma 4 31B it below it. One more model needs much the same memory: GLM-4.5-Air. Mistral Small 4 (119B-2603) is also head to head with GLM-4.5-Air above it on the leaderboard and Qwen3 30B-A3B Instruct 2507 below it.

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 Qwen3.5 122B-A10B · 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