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Qwen3 32B vs Llama 3.3 70B: is the bigger model worth it?
Qwen3 32B fits one 24 GB card. Llama 3.3 70B needs about 45 GB. What you gain and lose with each, with estimated speeds and hardware costs.
For most people, Qwen3 32B is the better buy. It runs on one used 24 GB card, it's twice as fast, and with thinking mode it is as good or better at reasoning and code. Llama 3.3 70B earns its extra memory on broad general knowledge, polished writing and following long, detailed instructions, and only if you already have the hardware or want it for other reasons.
Side by side
| Qwen3 32B | Llama 3.3 70B | |
|---|---|---|
| Made by | Alibaba (Qwen) | Meta |
| Released | April 2025 | December 2024 |
| Parameters | 32B, dense | 70B, dense |
| Download (Ollama, 4-bit) | ~20 GB | ~43 GB |
| Memory needed | ~22 GB | ~45 GB |
| Thinking mode | Yes | No |
| Context | 32K, 128K with YaRN | 128K |
| License | Apache 2.0 | Llama 3.3 Community License |
Hardware and speed
Both are dense, so every token reads the whole model from memory. Twice the size means roughly half the speed on the same hardware. Estimates from our calculator:
| Hardware | Qwen3 32B | Llama 3.3 70B | Used price |
|---|---|---|---|
| RTX 3090, 24 GB | ~26 tok/s | does not fit | $650 to $850 card |
| 2× RTX 3090, 48 GB | ~26 tok/s | ~12 tok/s | $1,900 to $2,500 build |
| RTX A6000, 48 GB | ~21 tok/s | ~10 tok/s | check current used prices |
| M1 Max, 64 GB | ~11 tok/s | ~5 tok/s | $1,500 to $2,100 Mac Studio |
| M1 Ultra, 128 GB | ~22 tok/s | ~10 tok/s | check current used prices |
Two cards split a model by layers, so they run at about one card's speed, which is why two 3090s don't double Qwen3 32B's speed. Prices are from our builds page.
The jump that matters: Qwen3 32B runs on a single-card desktop around $900 to $1,200. Llama 3.3 70B needs the two-card build or a big Mac. That's at least twice the money for a model that is slower.
Where Qwen3 32B wins
- Reasoning and math. With
/thinkit works through problems step by step. Llama 3.3 has no thinking mode. - Code. It's the strongest single-card coder we track. See best local LLM for coding.
- Speed. About 26 tok/s on a 3090 is comfortable reading speed. Llama 3.3 at 10 to 12 tok/s is usable but you notice the wait, especially with long answers.
- License. Apache 2.0 is simpler. See open model licenses explained.
Where Llama 3.3 70B wins
- Knowledge. More than twice the parameters means more facts stored. On general questions about less common topics it's less likely to make things up.
- Writing and tone. It writes naturally and follows style instructions well.
- Long, detailed instructions. Give it a page of rules and it tends to keep to them.
- Long context out of the box. 128K without extra settings, though on 48 GB you have only a few gigabytes left for it. A 70B model's context also costs more memory per token than a 32B's.
The middle option
If you have 24 GB and want more knowledge than Qwen3 32B, look at a mixture-of-experts model instead of a bigger dense one. Qwen3 30B-A3B is about six times faster on the same card. And if you can reach 96 GB or more, gpt-oss 120B is both smarter and faster than Llama 3.3 70B on most Macs. See mixture of experts explained.
Our take
- One 24 GB card: Qwen3 32B. No contest, since Llama 3.3 70B doesn't fit.
- 48 GB already: keep both. Use Qwen3 32B for code and reasoning, Llama 3.3 70B for writing and general questions.
- Buying hardware just for Llama 3.3 70B: read the Llama 3.3 70B hardware guide first, and price the two-card build against a big-memory Mac.
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