gpt-oss-20b vs Ministral 3 14B
gpt-oss-20b scores higher on the intelligence index, 9 against 6. Both take the same machine to start: the cheapest here that runs either is the Mac mini M6, 24GB, at $1,099. On it, gpt-oss-20b is about 1.9× quicker: 18 tok/s against 9.4, both estimated from memory bandwidth. At 500k tokens a day the Mac mini M6, 24GB pays for itself in 34 years running Ministral 3 14B, against 426 years running gpt-oss-20b.
| gpt-oss-20b | Ministral 3 14B | |
|---|---|---|
| Intelligence index | 9 | 6 |
| Class | Below every hosted tier | Below every hosted tier |
| Weights | 12 GB | 8.2 GB |
| Needs at 32k | 13 GB | 14 GB |
| Quantisation | MXFP4 | Q4_K_M |
| Parameters | 20.9B (3.6B active) | 14B |
| Max context | 128k | 256k |
| API price per 1M | $0.02 in / $0.1 out | $0.2 in / $0.2 out |
| Licence | Apache 2.0 | Apache 2.0 |
| Machines here that run it | 33 of 37 | 33 of 37 |
| Cheapest machine that runs it | Mac mini M6, 24GB $1,099 | Mac mini M6, 24GB $1,099 |
| Summarising | good | not rated |
| Translation | usable | not rated |
| Everyday coding | good | not rated |
| Reasoning & maths | usable | not rated |
| Agentic work | usable | not rated |
Run gpt-oss-20b on the Mac mini M6, 24GB · or Ministral 3 14B
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 Mac mini M6, 24GB
The cheapest machine that runs either model is the same one, so this is the pair doing the same work on the same hardware: Mac mini M6, 24GB, at $1,099.
| gpt-oss-20b | Ministral 3 14B | |
|---|---|---|
| Speed at 32k | 18 tok/s estimated | 9.4 tok/s estimated |
| Pay-back on this machine | Pays back in 426 years | Pays back in 34 years |
| API cost per month | $0.38 | $3.04 |
Run gpt-oss-20b on the Mac mini M6, 24GB · or Ministral 3 14B
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 Mac mini M6, 24GB. Ministral 3 14B 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 use | gpt-oss-20b | Ministral 3 14B |
|---|---|---|
| 50ka few chats a day | 4,263 years | 335 years |
| 200klight assistant use | 1,066 years | 84 years |
| 1Ma moderate coding-assistant day | 213 years | 17 years |
| 4Mheavy coding with an agent | 53 years | 4.2 years |
| 20Magents running most of the day | 11 years | 16 monthsits ceiling |
The Mac mini M6, 24GB generates at most 13M tokens a day on Ministral 3 14B, 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 gpt-oss-20b at 20M tokens a day · or Ministral 3 14B
Memory is not what separates them
gpt-oss-20b needs 13 GB of memory at 32k of context and Ministral 3 14B needs 14 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.
gpt-oss-20b is also head to head with Qwen3-Coder Next above it on the leaderboard and Gemma 4 E4B below it. Ministral 3 14B is also head to head with Llama 4 Scout 17B-16E above it on the leaderboard and Qwen3 8B below it. One more model needs much the same memory: Qwen3 14B.
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 gpt-oss-20b · every machine that runs Ministral 3 14B · every other match-up · both against the frontier · the quickest pay-back at each level of use