Qwen3-Coder Next vs DeepSeek-R1-Distill-Llama-70B

Qwen3-Coder Next scores higher on the intelligence index, 10 against 8. Both take the same machine to start: the cheapest here that runs either is the Framework Desktop, 128GB, at $3,449. On it, Qwen3-Coder Next is about 13.5× quicker: 54 tok/s against 4, DeepSeek-R1-Distill-Llama-70B's measured and the other estimated from memory bandwidth. At 500k tokens a day the Framework Desktop, 128GB pays for itself in 27 years running DeepSeek-R1-Distill-Llama-70B, against 122 years running Qwen3-Coder Next.

Run Qwen3-Coder Next on the Framework Desktop, 128GB · or DeepSeek-R1-Distill-Llama-70B

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-Coder Next on the Framework Desktop, 128GB · or DeepSeek-R1-Distill-Llama-70B

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. DeepSeek-R1-Distill-Llama-70B pays for it sooner at every level of use, so which of them to run does not turn on how hard you work it.

The Framework Desktop, 128GB generates at most 5.49M tokens a day on DeepSeek-R1-Distill-Llama-70B, 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-Coder Next at 20M tokens a day · or DeepSeek-R1-Distill-Llama-70B

Memory is not what separates them

Qwen3-Coder Next needs 49 GB of memory at 32k of context and DeepSeek-R1-Distill-Llama-70B needs 53 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-Coder Next is also head to head with Qwen3-Coder 30B-A3B above it on the leaderboard and gpt-oss-20b below it. DeepSeek-R1-Distill-Llama-70B is also head to head with DeepSeek-R1-Distill-Qwen-32B above it on the leaderboard and Llama 3.3 70B Instruct 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-Coder Next · every machine that runs DeepSeek-R1-Distill-Llama-70B · every other match-up · both against the frontier · the quickest pay-back at each level of use