Uncensored · 11 GPUs measured first-party · llama.cpp · Updated October 2026
Uncensored on 11 GPUs, measured first-party: NVIDIA B300 leads at 159.5 tok/s, T4 trails at 18.9 tok/s, and it peaked at 10GB of VRAM.
Benchmarked weights: bartowski/Qwen2.5-14B_Uncensored_Instruct-GGUF

159.5 tok/s on Uncensored, the ceiling. Measured on our bench. 288GB of VRAM, $40,000 at launch.

135.7 tok/s on Uncensored, lowest launch price that still fits. Measured on our bench. 96GB of VRAM, $8,565 at launch.
What GPU Do You Need for Uncensored?, 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.
Uncensored. Measured tokens per second by GPU
| GPU | tok/s | Prompt t/s | tok/W | Avg power |
|---|---|---|---|---|
| NVIDIA B300 | 159.5 | 3164.6 | 0.38 | 416.4 W |
| NVIDIA B200 | 150.5 | 5322.8 | 0.35 | 433.2 W |
| NVIDIA H200 | 148.7 | 4698.8 | 0.51 | 289.3 W |
| NVIDIA H100 80GB HBM3 | 144.9 | 4717.1 | 0.52 | 278.8 W |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | 135.7 | 7098 | 0.5 | 272.7 W |
| NVIDIA A100 80GB SXM4 | 89.43 | 2469.7 | 0.42 | 211.4 W |
| NVIDIA A100 40GB SXM4 | 85.82 | 2500.6 | 0.46 | 188.1 W |
| NVIDIA L40S | 74.31 | 5245.6 | 0.31 | 236.1 W |
| NVIDIA A10G | 47.45 | 1818.7 | 0.38 | 124.2 W |
| NVIDIA L4 | 27.29 | 1550.7 | 0.42 | 64.7 W |
| NVIDIA T4 | 18.94 | 659.6 | 0.29 | 64.6 W |
What the numbers show. Across 11 GPUs measured on our own bench, B300 is fastest at 159 tok/s. The slowest, T4, manages 18.9, so the spread is 8.4x from top to bottom. H100 80GB HBM3 is the most efficient, 145 tok/s at 279W. Per dollar of launch price, A10G gives the most (16.9 tok/s per $1,000). The fastest card with 16GB or less is T4 at 18.9 tok/s.
How it compares. H100 80GB HBM3: Uncensored 144.9 tok/s, Qwen2.5-Coder-14B 144.8 (15B), Qwen2.5-Coder-14B-Instruct-abliterated 145.0, DeepSeek-R1 Distill 14B 144.8, Qwen2.5-14B 144.7 (15B). 1 of 4 beat Uncensored here.
Cost on a rented GPU. 1M generated tokens of Uncensored: $1.53 on a A100 40GB SXM4 ($0.47/hr, 3.2 hours), $12.09 on a B300 ($6.94/hr, 105 min, 7.9x the cost).
Uncensored: 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 | 85.82 | $1.53 |
| NVIDIA T4 | $0.14/hr | 18.94 | $1.99 |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | $1.08/hr | 135.7 | $2.20 |
| NVIDIA A100 80GB SXM4 | $0.95/hr | 89.43 | $2.94 |
| NVIDIA L40S | $0.79/hr | 74.31 | $2.95 |
| NVIDIA H100 80GB HBM3 | $2.14/hr | 144.9 | $4.09 |
| NVIDIA L4 | $0.44/hr | 27.29 | $4.48 |
| NVIDIA H200 | $3.59/hr | 148.7 | $6.71 |
| NVIDIA B200 | $5.98/hr | 150.5 | $11.04 |
| NVIDIA B300 | $6.94/hr | 159.5 | $12.09 |
Cheapest hourly rate we track on RunPod and Vast.ai, divided by the measured speed. Startup time and storage are extra.
Speed tiers for Uncensored. 30+ tok/s: 9 (B300, B200, H200); 10-30 tok/s: 2 (L4, T4). 30 tok/s is roughly where replies outpace reading.
Reading your prompt. Before Uncensored writes anything it reads the input: 7098.0 tok/s on the RTX PRO 6000 Blackwell Workstation Edition (0.6s for a 4,000-token prompt), 659.6 on the T4 (6.1s). Long documents and big code files feel this number more than the generation speed.
VRAM for Uncensored. Measured peak 8.9GB, so 12GB is the smallest common card size; smallest card it ran on: T4 (16GB). With long context: Q4_K_M 12GB (tested), Q2_K 8GB, Q3_K_M 10GB, Q5_K_M 15GB, Q6_K 17GB.
Power on Uncensored. Most efficient: H100 80GB HBM3, 279W, 0.53 kWh per 1M generated tokens. Hungriest: B200, 433W, 0.80 kWh. At $0.15/kWh: $0.080 per 1M generated tokens.
Fastest on Uncensored: NVIDIA B300, 159.5 tok/s. Cheapest to rent per job: NVIDIA A100 40GB SXM4, $1.53 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.