Qwen3-30B-A3B · 10 GPUs measured first-party · llama.cpp · Updated October 2026
Qwen3-30B-A3B on 10 GPUs, measured first-party: NVIDIA RTX PRO 6000 Blackwell Workstation Edition leads at 311.8 tok/s, L4 trails at 95 tok/s, and it peaked at 20GB of VRAM.
Benchmarked weights: bartowski/Qwen_Qwen3-30B-A3B-GGUF

311.8 tok/s on Qwen3-30B-A3B, the ceiling. Measured on our bench. 96GB of VRAM, $8,565 at launch.
What GPU Do You Need for Qwen3-30B-A3B?, tok/s by GPU
Efficiency: tok/s per 100W drawn
Power is the average pulled during the run, sampled at 1Hz. The fastest card is often not the one here, and for anything left running this is the number that shows up on the bill.
Value: tok/s per $1,000 of MSRP
Launch price, not street price, so it ages. A speed leaderboard always crowns the most expensive card; this is the counterweight.
Qwen3-30B-A3B. Measured tokens per second by GPU
| GPU | tok/s | Prompt t/s | tok/W | Avg power |
|---|---|---|---|---|
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | 311.8 | 9821.3 | 2.16 | 144.5 W |
| NVIDIA H200 | 293.5 | 7430.5 | 1.86 | 158.1 W |
| NVIDIA B300 | 291.8 | 4783.2 | 1.02 | 287.3 W |
| NVIDIA H100 80GB HBM3 | 285.4 | 7386.3 | 1.79 | 159.5 W |
| NVIDIA B200 | 271.7 | 7653 | 0.9 | 300.4 W |
| NVIDIA L40S | 214.1 | 8183 | 1.7 | 126.1 W |
| NVIDIA A100 80GB SXM4 | 178.1 | 3722.6 | 1.22 | 146.4 W |
| NVIDIA A100 40GB SXM4 | 167.1 | 3730.1 | 1.58 | 105.6 W |
| NVIDIA A10G | 140.1 | 2755.2 | 1.45 | 96.7 W |
| NVIDIA L4 | 95.02 | 2491.5 | 1.87 | 50.9 W |
What the numbers show. Across 10 GPUs measured on our own bench, RTX PRO 6000 Blackwell Workstation Edition is fastest at 312 tok/s. The slowest, L4, manages 95.0, so the spread is 3.3x from top to bottom. Per dollar of launch price, A10G gives the most (50.0 tok/s per $1,000).
How it compares. H100 80GB HBM3: Qwen3-30B-A3B 285.4 tok/s, Llama-2-7B 284.6 (7B), Qwen3 30B A3B 283.8 (31B), Gemma 3 4B 289.6, DeepSeek Coder 7B Instruct v1.5 293.9 (7B). 2 of 4 beat Qwen3-30B-A3B here.
Cost on a rented GPU. 1M generated tokens of Qwen3-30B-A3B: $0.78 on a A100 40GB SXM4 ($0.47/hr, 100 min), $0.96 on a RTX PRO 6000 Blackwell Workstation Edition ($1.08/hr, 53 min, 1.2x the cost).
Qwen3-30B-A3B: cost per 1M generated tokens on rented GPUs
| GPU | Cheapest rate | Speed (tok/s) | Cost per 1M generated tokens |
|---|---|---|---|
| NVIDIA A100 40GB SXM4 | $0.47/hr | 167.1 | $0.78 |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | $1.08/hr | 311.8 | $0.96 |
| NVIDIA L40S | $0.79/hr | 214.1 | $1.03 |
| NVIDIA L4 | $0.44/hr | 95.02 | $1.29 |
| NVIDIA A100 80GB SXM4 | $0.95/hr | 178.1 | $1.48 |
| NVIDIA H100 80GB HBM3 | $2.14/hr | 285.4 | $2.08 |
| NVIDIA H200 | $3.59/hr | 293.5 | $3.40 |
| NVIDIA B200 | $5.98/hr | 271.7 | $6.11 |
| NVIDIA B300 | $6.94/hr | 291.8 | $6.61 |
Cheapest hourly rate we track on RunPod and Vast.ai, divided by the measured speed. Startup time and storage are extra.
Speed tiers for Qwen3-30B-A3B. 30+ tok/s: 10 (RTX PRO 6000 Blackwell Workstation Edition, H200, B300). 30 tok/s is roughly where replies outpace reading.
Reading your prompt. Before Qwen3-30B-A3B writes anything it reads the input: 9821.3 tok/s on the RTX PRO 6000 Blackwell Workstation Edition (0.4s for a 4,000-token prompt), 2491.5 on the L4 (1.6s). Long documents and big code files feel this number more than the generation speed.
VRAM for Qwen3-30B-A3B. Measured peak 18.2GB, so 24GB is the smallest common card size; smallest card it ran on: A10G (24GB). With long context: Q4_K_M 24GB (tested), Q2_K 15GB, Q3_K_M 19GB, Q5_K_M 29GB, Q6_K 33GB.
Power on Qwen3-30B-A3B. Most efficient: RTX PRO 6000 Blackwell Workstation Edition, 144W, 0.13 kWh per 1M generated tokens. Hungriest: B200, 300W, 0.31 kWh. At $0.15/kWh: $0.019 per 1M generated tokens.
Fastest on Qwen3-30B-A3B: NVIDIA RTX PRO 6000 Blackwell Workstation Edition, 311.8 tok/s. Cheapest to rent per job: NVIDIA A100 40GB SXM4, $0.78 per 1M generated tokens.
llama.cpp llama-bench at Q4_K_M, 512-token prompt and 128 generated tokens, three runs after a warmup, full GPU offload, with power and VRAM sampled throughout. Token generation is memory-bandwidth-bound, so the ranking tracks bandwidth closely, which makes it a fair guide to cards we haven't run yet.