Qwen3-30B-A3B-Instruct-2507
2recorded runs
312.9best tok/s
0verified
What the Qwen3-30B-A3B-Instruct-2507 numbers mean
The fastest result on our board is 312.9 output tok/s on an RTX 5090 at Q4_K_M with a 2048-token context. That is about 3.2 ms per generated token — 500 tokens takes roughly 1.6 seconds. Prompt processing on the same record runs at 1108.1 tok/s, so a 2,000-token prompt is read in about 1.8 seconds. Across the 2 records we hold for this model the range is 100.5–312.9 tok/s on 2 GPUs, because quantisation, context length and the engine build all move the number.
How much VRAM does Qwen3-30B-A3B-Instruct-2507 need?
Qwen3-30B-A3B-Instruct-2507 has 31.0B parameters. These estimates use the same formula as the VRAM calculator: weights, plus about 15% for a moderate-context KV cache and runtime overhead, plus a small engine floor.
| Quantisation | Estimated VRAM | Smallest card that fits |
|---|---|---|
| Q4_K_M (4-bit) | 20.9 GB | 32 GB |
| Q8_0 (8-bit) | 38.7 GB | 48 GB |
| FP16 (16-bit) | 72.1 GB | 96 GB |
Fastest GPUs for this model (best tok/s)
- RTX 5090312.9
- Intel Arc Pro B70100.5
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| QUEST-30B-RL-B70-Turbo | 31B | 17.4 GB |
| Qwen3-30B-A3B-Thinking-2507 | 31B | 17.4 GB |
| Hy-MT2-30B-A3B | 30B | 16.9 GB |
| Muse-Glimmer-30B | 30B | 16.9 GB |
| Nemotron-3-Nano-Omni-30B-A3B-Reasoning | 30B | 16.9 GB |
| Nemotron-Cascade-2-30B-A3B | 32B | 18.0 GB |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| RTX 5090 · 32 GB | Qwen3-30B-A3B-Instruct-2507 | Q4_K_M | lmstudio — | 2048 | 312.9 … | 1108.1 | — | src |
| Intel Arc Pro B70 · 32 GB | Qwen3-30B-A3B-Instruct-2507 | Q4_K_XL | llama.cpp — | 2048 | 100.5 … | 1464.1 | — | src |