Llama 3.1 8B Instruct vs Qwen3 32B
Llama 3.1 8B Instruct and Qwen3 32B both score 7 on the intelligence index. The cheapest machine here that runs Qwen3 32B is the Radeon AI PRO R9700, 32GB, at $1,299. Llama 3.1 8B Instruct runs on the Mac mini M6, 16GB at $899, $400 less. The Radeon AI PRO R9700, 32GB is priced as the card alone, without the PC around it. On the Radeon AI PRO R9700, 32GB, the cheapest machine here that runs both, Llama 3.1 8B Instruct is about 3× quicker: 60 tok/s against 20, Qwen3 32B's measured and the other estimated from memory bandwidth. At 500k tokens a day the Radeon AI PRO R9700, 32GB pays for itself in 150 years running Qwen3 32B, against 1,078 years running Llama 3.1 8B Instruct.
| Llama 3.1 8B Instruct | Qwen3 32B | |
|---|---|---|
| Intelligence index | 7 | 7 |
| Class | Below every hosted tier | Below every hosted tier |
| Weights | 4.9 GB | 20 GB |
| Needs at 32k | 9.2 GB | 28 GB |
| Quantisation | Q4_K_M | Q4_K_M |
| Parameters | 8B | 32.8B |
| Max context | 128k | 40k |
| API price per 1M | $0.02 in / $0.04 out | $0.08 in / $0.28 out |
| Licence | Llama 3.1 Community License | Apache 2.0 |
| Machines here that run it | 37 of 37 | 26 of 37 |
| Cheapest machine that runs it | Mac mini M6, 16GB $899 | AMD Radeon AI PRO R9700, 32GB $1,299card only |
| Summarising | good | good |
| Translation | usable | good |
| Everyday coding | usable | good |
| Reasoning & maths | don’t | usable |
| Agentic work | don’t | usable |
Run Llama 3.1 8B Instruct on the Mac mini M6, 16GB · or Qwen3 32B on the Radeon AI PRO R9700, 32GB
Ratings are coarse on purpose: they say what a model is usable for, not where it places to the decimal.
Jump to: Side by side on the Radeon AI PRO R9700, 32GB · How much use it takes to pay for the machine · Machines that run one and not the other · The assumptions behind both columns
Side by side on the Radeon AI PRO R9700, 32GB
The table above gives each model the cheapest machine that runs it, and those are two different machines, so nothing in it is a like-for-like race. The AMD Radeon AI PRO R9700, 32GB is the cheapest machine here that runs both, so this is the pair doing the same work on the same hardware.
| Llama 3.1 8B Instruct | Qwen3 32B | |
|---|---|---|
| Speed at 32k | 60 tok/s estimated | 20 tok/s measured |
| Pay-back on this machine | Pays back in 1,078 years | Pays back in 150 years |
| API cost per month | $0.32 | $1.41 |
Run Llama 3.1 8B Instruct on the Radeon AI PRO R9700, 32GB · or Qwen3 32B
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 Radeon AI PRO R9700, 32GB. Qwen3 32B 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 | Llama 3.1 8B Instruct | Qwen3 32B |
|---|---|---|
| 50ka few chats a day | 10,783 years | 1,499 years |
| 200klight assistant use | 2,696 years | 375 years |
| 1Ma moderate coding-assistant day | 539 years | 75 years |
| 4Mheavy coding with an agent | 135 years | 19 years |
| 20Magents running most of the day | 27 years | 3.7 years |
Run Llama 3.1 8B Instruct at 20M tokens a day · or Qwen3 32B
Machines that run one and not the other
Llama 3.1 8B Instruct needs 9.2 GB of memory at 32k of context and Qwen3 32B needs 28 GB. That puts Llama 3.1 8B Instruct on 11 of the 37 machines priced here that Qwen3 32B does not, starting at $899.
| Machine | Price | Memory | Speed on Llama 3.1 8B Instruct | Pay-back |
|---|---|---|---|---|
| Mac mini M6, 16GB | $899 | 16 GB | 12 tok/s estimated | Pays back in 842 years |
| Mac mini M6, 24GB | $1,099 | 24 GB | 14 tok/s estimated | Pays back in 815 years |
| Strix Halo Framework Desktop, 32GB | $1,269 | 32 GB | 21 tok/s estimated | Pays back in 2,883 years |
| Mac mini M6, 32GB | $1,299 | 32 GB | 14 tok/s estimated | Pays back in 963 years |
| MacBook Air M5 (13-inch), 16GB | $1,299 | 16 GB | 12 tok/s estimated | Pays back in 1,217 years |
| MacBook Air M5 (15-inch), 16GB | $1,499 | 16 GB | 12 tok/s estimated | Pays back in 1,404 years |
5 more, on the Llama 3.1 8B Instruct page.
Llama 3.1 8B Instruct is also head to head with Devstral Small 2 24B above it on the leaderboard. One more model needs much the same memory: Ministral 3 8B. Qwen3 32B is also head to head with Mistral Small 3.2 24B Instruct below it on the leaderboard and Qwen3.8 27B, the current Qwen nearest it in size. One more model needs much the same memory: DeepSeek-R1-Distill-Qwen-32B.
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 Llama 3.1 8B Instruct · every machine that runs Qwen3 32B · every other match-up · both against the frontier · the quickest pay-back at each level of use