phi-2 · 11 GPUs measured first-party · llama.cpp · Updated October 2026

What GPU Do You Need for phi-2?

phi-2 on 11 GPUs, measured first-party: NVIDIA RTX PRO 6000 Blackwell Workstation Edition leads at 410.1 tok/s, T4 trails at 89.6 tok/s, and it peaked at 3GB of VRAM.

Benchmarked weights: TheBloke/phi-2-GGUF

Fastest we measured
NVIDIA RTX PRO 6000 Blackwell Workstation Edition

NVIDIA RTX PRO 6000 Blackwell Workstation Edition

410.1 tok/s on phi-2, the ceiling. Measured on our bench. 96GB of VRAM, $8,565 at launch.

Pros
  • 410.1 tok/s on phi-2
  • 96GB, clears the phi-2 floor
  • Rentable by the hour rather than bought
Cons
  • 600W board rating
  • Datacenter or workstation hardware, not a retail purchase
410.1tok/s
Fastest: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
measured, 3-run average
~3GB
VRAM needed (measured peak)
GPU-independent, applies to every card
11
GPUs measured
same pinned harness
2.51tok/s/W
Most efficient: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
real power sampling, not TDP

What GPU Do You Need for phi-2?, tok/s by GPU

NVIDIA RTX PRO 6000 Blackwell Workstation Edition
410.1 tok/s
NVIDIA B300
356.6 tok/s
NVIDIA B200
348.7 tok/s
NVIDIA H200
347.1 tok/s
NVIDIA H100 80GB HBM3
340.1 tok/s
NVIDIA L40S
283.3 tok/s
NVIDIA A100 80GB SXM4
235.6 tok/s
NVIDIA A100 40GB SXM4
228.1 tok/s
NVIDIA A10G
172.4 tok/s
NVIDIA L4
115 tok/s
NVIDIA T4
89.6 tok/s

Efficiency: tok/s per 100W drawn

NVIDIA RTX PRO 6000 Blackwell Workstation Edition
250.68 tok/s / 100W
NVIDIA L4
203.16 tok/s / 100W
NVIDIA H200
181.34 tok/s / 100W
NVIDIA H100 80GB HBM3
180.04 tok/s / 100W
NVIDIA L40S
177.82 tok/s / 100W
NVIDIA A100 40GB SXM4
174.66 tok/s / 100W
NVIDIA T4
157.47 tok/s / 100W
NVIDIA A10G
154.39 tok/s / 100W
NVIDIA A100 80GB SXM4
146.67 tok/s / 100W
NVIDIA B300
112.97 tok/s / 100W
NVIDIA B200
107.33 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
61.59 tok/s / $1k
NVIDIA RTX PRO 6000 Blackwell Workstation Edition
47.88 tok/s / $1k
NVIDIA L4
46 tok/s / $1k
NVIDIA T4
38.97 tok/s / $1k
NVIDIA L40S
37.77 tok/s / $1k
NVIDIA A100 40GB SXM4
19.01 tok/s / $1k
NVIDIA A100 80GB SXM4
13.86 tok/s / $1k
NVIDIA H100 80GB HBM3
11.34 tok/s / $1k
NVIDIA H200
11.2 tok/s / $1k
NVIDIA B300
8.92 tok/s / $1k
NVIDIA B200
8.72 tok/s / $1k

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

phi-2. Measured tokens per second by GPU

NVIDIA RTX PRO 6000 Blackwell Workstation Edition410.1
NVIDIA B300356.6
NVIDIA B200348.7
NVIDIA H200347.1
NVIDIA H100 80GB HBM3340.1
NVIDIA L40S283.3
NVIDIA A100 80GB SXM4235.6
NVIDIA A100 40GB SXM4228.1
NVIDIA A10G172.4
NVIDIA L4115
NVIDIA T489.6
GPUtok/sPrompt t/stok/WAvg power
NVIDIA RTX PRO 6000 Blackwell Workstation Edition410.123325.52.51163.6 W
NVIDIA B300356.612472.81.13315.7 W
NVIDIA B200348.717015.91.07324.9 W
NVIDIA H200347.115933.91.81191.4 W
NVIDIA H100 80GB HBM3340.116241.31.8188.9 W
NVIDIA L40S283.3198431.78159.3 W
NVIDIA A100 80GB SXM4235.69397.71.47160.6 W
NVIDIA A100 40GB SXM4228.17715.81.75130.6 W
NVIDIA A10G172.465861.54111.7 W
NVIDIA L41156812.82.0356.6 W
NVIDIA T489.62732.21.5756.9 W

What the numbers show. Across 11 GPUs measured on our own bench, RTX PRO 6000 Blackwell Workstation Edition is fastest at 410 tok/s. The slowest, T4, manages 89.6, so the spread is 4.6x from top to bottom. Per dollar of launch price, A10G gives the most (61.6 tok/s per $1,000). The fastest card with 16GB or less is T4 at 89.6 tok/s.

About phi-2. phi-2: from microsoft, 2.8B parameters, on Hugging Face since December 2023, MIT licence. 620,473 downloads in the last 30 days.

How it compares. H100 80GB HBM3: phi-2 340.1 tok/s, gemma-2-2b 392.3 (3B), MiniCPM5 2B 428.7 (3B), SmolLM3 3B 398.0 (3B), Qwen2.5-3B 395.5 (3B). All 4 beat phi-2 here.

Cost on a rented GPU. 1M generated tokens of phi-2: $0.42 on a T4 ($0.14/hr, 3.1 hours), $0.73 on a RTX PRO 6000 Blackwell Workstation Edition ($1.08/hr, 41 min, 1.7x the cost).

phi-2: 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 B200$5.98/hr
NVIDIA B300$6.94/hr
GPUCheapest rateSpeed (tok/s)Cost per 1M generated tokens
NVIDIA T4$0.14/hr89.6$0.42
NVIDIA A100 40GB SXM4$0.47/hr228.1$0.57
NVIDIA RTX PRO 6000 Blackwell Workstation Edition$1.08/hr410.1$0.73
NVIDIA L40S$0.79/hr283.3$0.77
NVIDIA L4$0.44/hr115$1.06
NVIDIA A100 80GB SXM4$0.95/hr235.6$1.12
NVIDIA H100 80GB HBM3$2.14/hr340.1$1.74
NVIDIA H200$3.59/hr347.1$2.87
NVIDIA B200$5.98/hr348.7$4.76
NVIDIA B300$6.94/hr356.6$5.41

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

Speed tiers for phi-2. 30+ tok/s: 11 (RTX PRO 6000 Blackwell Workstation Edition, B300, B200). 30 tok/s is roughly where replies outpace reading.

Reading your prompt. Before phi-2 writes anything it reads the input: 23325.5 tok/s on the RTX PRO 6000 Blackwell Workstation Edition (0.2s for a 4,000-token prompt), 2732.2 on the T4 (1.5s). Long documents and big code files feel this number more than the generation speed.

VRAM for phi-2. Measured peak 2.4GB, so 8GB is the smallest common card size; smallest card it ran on: T4 (16GB). With long context: Q4_K_M 3GB (tested), Q2_K 2GB, Q3_K_M 3GB, Q5_K_M 4GB, Q6_K 4GB.

Power on phi-2. Most efficient: RTX PRO 6000 Blackwell Workstation Edition, 164W, 0.11 kWh per 1M generated tokens. Hungriest: B200, 325W, 0.26 kWh. At $0.15/kWh: $0.017 per 1M generated tokens.

Our verdict

Fastest on phi-2: NVIDIA RTX PRO 6000 Blackwell Workstation Edition, 410.1 tok/s. Cheapest to rent per job: NVIDIA T4, $0.42 per 1M generated tokens.

FAQ

What GPU do I need to run phi-2?
About 3GB. Smallest card that ran it: NVIDIA T4 (16GB).
How much does it cost to run phi-2 in the cloud?
$0.42 per 1M generated tokens on a NVIDIA T4 at $0.14/hr, cheapest of 10 rentable cards we measured.
Can I run phi-2 on a 12GB, 16GB or 24GB card?
It used 2.4GB at the precision we tested. 12GB: yes; 16GB: yes; 24GB: yes.
Is the H100 80GB HBM3 or the A100 80GB SXM4 faster for phi-2?
The H100 80GB HBM3: 340.1 vs 235.6 tok/s, 44% 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.