Llama-3.1-8B-Instruct vs Qwen3-8B: VRAM and speed for running locally
Side by side: how much memory each model needs at Q4, Q8 and FP16, how the KV cache grows with context, the cheapest GPU and Mac that run each, and estimated speed on 11 common machines.
Llama-3.1-8B-Instruct is lighter: about 6.6 GB at Q4 against 6.7 GB for Qwen3-8B, though both run on 81 of the devices we track. It should also be faster on the same hardware, since it reads 8.0B parameters per token against 8.2B. Which one gives better answers depends on your task, so check benchmarks for that; this page covers what it takes to run them.
| Llama-3.1-8B-Instruct | Qwen3-8B | |
|---|---|---|
| Maker | meta-llama | Qwen |
| License | llama3.1 | apache-2.0 |
| Type | Dense | Dense |
| Total parameters | 8.0B | 8.2B |
| Active per token | 8.0B all | 8.2B all |
| Memory at Q4_K_M | 6.6 GB | 6.7 GB |
| Memory at Q8_0 | 10.8 GB | 11.0 GB |
| Memory at FP16 | 19.5 GB | 19.8 GB |
| KV cache growth | 131 MB per 1k tokens, FP16 | 147 MB per 1k tokens, FP16 |
| Memory at Q4, 32k context | 10.4 GB 4.3 GB cache | 10.9 GB 4.8 GB cache |
| Cheapest GPU at Q4 | Intel Arc B570 $219 | Intel Arc B570 $219 |
| Cheapest Mac / mini PC at Q4 | Mac mini M6 16GB $899 | Mac mini M6 16GB $899 |
| Cheapest GPU at Q8 | Radeon RX 7600 XT $329 | Radeon RX 7600 XT $329 |
| Tracked devices that run it at Q4 | 81 of 82 | 81 of 82 |
Estimated speed on the same hardware
| Device | Llama-3.1-8B-Instruct | Qwen3-8B |
|---|---|---|
| GeForce RTX 3060 12GB12 GB usable · 360 GB/s · $329 | 44–63 | 43–62 |
| GeForce RTX 4060 Ti 16GB16 GB usable · 288 GB/s · $499 | 35–50 | 35–49 |
| GeForce RTX 508016 GB usable · 960 GB/s · $999 | 118–168 | 116–164 |
| GeForce RTX 309024 GB usable · 936 GB/s · $1,499 | 115–163 | 113–160 |
| Radeon RX 7900 XTX24 GB usable · 960 GB/s · $999 | 118–168 | 116–164 |
| GeForce RTX 509032 GB usable · 1792 GB/s · $1,999 | 221–313 | 217–307 |
| Mac mini M6 24GB18 GB usable · 170 GB/s · $1,299 | 16–28 | 15–27 |
| Mac mini M6 32GB24 GB usable · 170 GB/s · $1,799 | 16–28 | 15–27 |
| Mac mini M5 Pro 64GB48 GB usable · 307 GB/s · $3,199 | 28–50 | 28–49 |
| Framework Desktop (Ryzen AI Max+ 395) 128GB96 GB usable · 256 GB/s · $3,449 | 24–42 | 23–41 |
| MacBook Pro M5 Max 128GB96 GB usable · 614 GB/s · $6,699 | 57–101 | 56–99 |
Quick answers
- Which needs less VRAM, Llama-3.1-8B-Instruct or Qwen3-8B?
- Llama-3.1-8B-Instruct: about 6.6 GB at Q4_K_M, against 6.7 GB for Qwen3-8B. At Q8_0 it's 10.8 GB vs 11.0 GB.
- Which is faster locally, Llama-3.1-8B-Instruct or Qwen3-8B?
- Decode speed is limited by how many bytes are read per token. Llama-3.1-8B-Instruct reads 8.0B parameters per token and Qwen3-8B reads 8.2B, so Llama-3.1-8B-Instruct should be faster on the same machine. Our estimate on the GeForce RTX 3060 12GB at Q4 is 44–63 tok/s vs 43–62 tok/s. These are estimates, not benchmarks.
- What is the cheapest GPU for Llama-3.1-8B-Instruct and Qwen3-8B?
- At Q4: Intel Arc B570 ($219) for Llama-3.1-8B-Instruct; Intel Arc B570 ($219) for Qwen3-8B. Prices are dated list-price snapshots.
- Can a Mac run Llama-3.1-8B-Instruct and Qwen3-8B?
- The cheapest Mac or mini PC we track for Llama-3.1-8B-Instruct is the Mac mini M6 16GB ($899). For Qwen3-8B it's the Mac mini M6 16GB ($899).
- Which is better, Llama-3.1-8B-Instruct or Qwen3-8B?
- We don't score answer quality. This comparison covers memory, context cache, hardware and speed. Pick the one that fits your hardware, then test both on your own prompts.
All comparisons · MoE vs dense · Q4 vs Q8 vs FP16 · Context length and VRAM · VRAM calculator