Qwen2-1.5B · 11 GPUs measured first-party · llama.cpp · Updated October 2026

What GPU Do You Need for Qwen2-1.5B?

Qwen2-1.5B on 11 GPUs, measured first-party: NVIDIA RTX PRO 6000 Blackwell Workstation Edition leads at 648.5 tok/s, T4 trails at 148 tok/s, and it peaked at 2GB of VRAM.

Benchmarked weights: Qwen/Qwen2-1.5B-Instruct-GGUF

Fastest we measured
NVIDIA RTX PRO 6000 Blackwell Workstation Edition

NVIDIA RTX PRO 6000 Blackwell Workstation Edition

648.5 tok/s on Qwen2-1.5B, the ceiling. Measured on our bench. 96GB of VRAM, $8,565 at launch.

Pros
  • 648.5 tok/s on Qwen2-1.5B
  • 96GB, clears the Qwen2-1.5B floor
  • Rentable by the hour rather than bought
Cons
  • 600W board rating
  • Datacenter or workstation hardware, not a retail purchase
648.5tok/s
Fastest: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
measured, 3-run average
~2GB
VRAM needed (measured peak)
GPU-independent, applies to every card
11
GPUs measured
same pinned harness
5.55tok/s/W
Most efficient: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
real power sampling, not TDP

What GPU Do You Need for Qwen2-1.5B?, tok/s by GPU

NVIDIA RTX PRO 6000 Blackwell Workstation Edition
648.5 tok/s
NVIDIA B300
583.8 tok/s
NVIDIA H200
546.5 tok/s
NVIDIA H100 80GB HBM3
536.5 tok/s
NVIDIA B200
454.6 tok/s
NVIDIA L40S
416.6 tok/s
NVIDIA A100 80GB SXM4
333.8 tok/s
NVIDIA A100 40GB SXM4
322.1 tok/s
NVIDIA A10G
265.4 tok/s
NVIDIA L4
189.2 tok/s
NVIDIA T4
147.7 tok/s

Efficiency: tok/s per 100W drawn

NVIDIA RTX PRO 6000 Blackwell Workstation Edition
554.74 tok/s / 100W
NVIDIA L4
363.81 tok/s / 100W
NVIDIA H200
354.85 tok/s / 100W
NVIDIA L40S
346.28 tok/s / 100W
NVIDIA A100 40GB SXM4
345.22 tok/s / 100W
NVIDIA H100 80GB HBM3
331.8 tok/s / 100W
NVIDIA A10G
277.38 tok/s / 100W
NVIDIA T4
268.51 tok/s / 100W
NVIDIA A100 80GB SXM4
258.55 tok/s / 100W
NVIDIA B300
220.46 tok/s / 100W
NVIDIA B200
157.99 tok/s / 100W

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

NVIDIA A10G
94.8 tok/s / $1k
NVIDIA RTX PRO 6000 Blackwell Workstation Edition
75.71 tok/s / $1k
NVIDIA L4
75.67 tok/s / $1k
NVIDIA T4
64.24 tok/s / $1k
NVIDIA L40S
55.54 tok/s / $1k
NVIDIA A100 40GB SXM4
26.84 tok/s / $1k
NVIDIA A100 80GB SXM4
19.63 tok/s / $1k
NVIDIA H100 80GB HBM3
17.88 tok/s / $1k
NVIDIA H200
17.63 tok/s / $1k
NVIDIA B300
14.59 tok/s / $1k
NVIDIA B200
11.36 tok/s / $1k

Launch price, not street price, so it ages. A speed leaderboard always crowns the most expensive card; this is the counterweight.

Qwen2-1.5B. Measured tokens per second by GPU

NVIDIA RTX PRO 6000 Blackwell Workstation Edition648.5
NVIDIA B300583.8
NVIDIA H200546.5
NVIDIA H100 80GB HBM3536.5
NVIDIA B200454.6
NVIDIA L40S416.6
NVIDIA A100 80GB SXM4333.8
NVIDIA A100 40GB SXM4322.1
NVIDIA A10G265.4
NVIDIA L4189.2
NVIDIA T4147.7
GPUtok/sPrompt t/stok/WAvg power
NVIDIA RTX PRO 6000 Blackwell Workstation Edition648.532854.15.55116.9 W
NVIDIA B300583.819899.12.2264.8 W
NVIDIA H200546.524510.83.55154.0 W
NVIDIA H100 80GB HBM3536.524454.73.32161.7 W
NVIDIA B200454.627266.11.58287.7 W
NVIDIA L40S416.626193.23.46120.3 W
NVIDIA A100 80GB SXM4333.812265.52.59129.1 W
NVIDIA A100 40GB SXM4322.111038.93.4593.3 W
NVIDIA A10G265.411800.32.7795.7 W
NVIDIA L4189.211181.83.6452.0 W
NVIDIA T4147.74823.22.6955.0 W

What the numbers show. Across 11 GPUs measured on our own bench, RTX PRO 6000 Blackwell Workstation Edition is fastest at 648 tok/s. The slowest, T4, manages 148, so the spread is 4.4x from top to bottom. Per dollar of launch price, A10G gives the most (94.8 tok/s per $1,000). The fastest card with 16GB or less is T4 at 148 tok/s.

About Qwen2-1.5B. Qwen2-1.5B: from Qwen, 1.5B parameters, on Hugging Face since June 2024, Apache 2.0 licence. 565,285 downloads in the last 30 days.

How it compares. H100 80GB HBM3: Qwen2-1.5B 536.5 tok/s, Qwen2.5-1.5B 537.2 (2B), Qwen2.5-Coder-1.5B 538.4 (2B), DeepSeek-R1 Distill 1.5B 537.3 (2B), Llama 3.2 1B 880.6 (1B). All 4 beat Qwen2-1.5B here.

Cost on a rented GPU. 1M generated tokens of Qwen2-1.5B: $0.26 on a T4 ($0.14/hr, 113 min), $0.46 on a RTX PRO 6000 Blackwell Workstation Edition ($1.08/hr, 26 min, 1.8x the cost).

Qwen2-1.5B: cost per 1M generated tokens on rented GPUs

NVIDIA T4$0.14/hr
NVIDIA A100 40GB SXM4$0.47/hr
NVIDIA RTX PRO 6000 Blackwell Workstation Edition$1.08/hr
NVIDIA L40S$0.79/hr
NVIDIA L4$0.44/hr
NVIDIA A100 80GB SXM4$0.95/hr
NVIDIA H100 80GB HBM3$2.14/hr
NVIDIA H200$3.59/hr
NVIDIA B300$6.94/hr
NVIDIA B200$5.98/hr
GPUCheapest rateSpeed (tok/s)Cost per 1M generated tokens
NVIDIA T4$0.14/hr147.7$0.26
NVIDIA A100 40GB SXM4$0.47/hr322.1$0.41
NVIDIA RTX PRO 6000 Blackwell Workstation Edition$1.08/hr648.5$0.46
NVIDIA L40S$0.79/hr416.6$0.53
NVIDIA L4$0.44/hr189.2$0.65
NVIDIA A100 80GB SXM4$0.95/hr333.8$0.79
NVIDIA H100 80GB HBM3$2.14/hr536.5$1.11
NVIDIA H200$3.59/hr546.5$1.82
NVIDIA B300$6.94/hr583.8$3.30
NVIDIA B200$5.98/hr454.6$3.65

Cheapest hourly rate we track on RunPod and Vast.ai, divided by the measured speed. Startup time and storage are extra.

Speed tiers for Qwen2-1.5B. 30+ tok/s: 11 (RTX PRO 6000 Blackwell Workstation Edition, B300, H200). 30 tok/s is roughly where replies outpace reading.

Reading your prompt. Before Qwen2-1.5B writes anything it reads the input: 32854.1 tok/s on the RTX PRO 6000 Blackwell Workstation Edition (0.1s for a 4,000-token prompt), 4823.2 on the T4 (0.8s). Long documents and big code files feel this number more than the generation speed.

VRAM for Qwen2-1.5B. Measured peak 1.7GB, so 8GB is the smallest common card size; smallest card it ran on: T4 (16GB). With long context: Q4_K_M 2GB (tested), Q2_K 2GB, Q3_K_M 2GB, Q5_K_M 2GB, Q6_K 3GB.

Power on Qwen2-1.5B. Most efficient: L4, 52W, 76.4 Wh per 1M generated tokens. Hungriest: B200, 288W, 0.18 kWh. At $0.15/kWh: $0.011 per 1M generated tokens.

Our verdict

Fastest on Qwen2-1.5B: NVIDIA RTX PRO 6000 Blackwell Workstation Edition, 648.5 tok/s. Cheapest to rent per job: NVIDIA T4, $0.26 per 1M generated tokens.

FAQ

What GPU do I need to run Qwen2-1.5B?
About 2GB. Smallest card that ran it: NVIDIA T4 (16GB).
How much does it cost to run Qwen2-1.5B in the cloud?
$0.26 per 1M generated tokens on a NVIDIA T4 at $0.14/hr, cheapest of 10 rentable cards we measured.
Can I run Qwen2-1.5B on a 12GB, 16GB or 24GB card?
It used 1.7GB at the precision we tested. 12GB: yes; 16GB: yes; 24GB: yes.
Is the H100 80GB HBM3 or the A100 80GB SXM4 faster for Qwen2-1.5B?
The H100 80GB HBM3: 536.5 vs 333.8 tok/s, 61% faster on our bench.

How we test

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.