gemma-3-1b · 11 GPUs measured first-party · llama.cpp · Updated October 2026

What GPU Do You Need for gemma-3-1b?

gemma-3-1b on 11 GPUs, measured first-party: NVIDIA RTX PRO 6000 Blackwell Workstation Edition leads at 567.1 tok/s, T4 trails at 157 tok/s, and it peaked at 2GB of VRAM.

Benchmarked weights: lmstudio-community/gemma-3-1b-it-GGUF

Fastest we measured
NVIDIA RTX PRO 6000 Blackwell Workstation Edition

NVIDIA RTX PRO 6000 Blackwell Workstation Edition

567.1 tok/s on gemma-3-1b, the ceiling. Measured on our bench. 96GB of VRAM, $8,565 at launch.

Pros
  • 567.1 tok/s on gemma-3-1b
  • 96GB, clears the gemma-3-1b floor
  • Rentable by the hour rather than bought
Cons
  • 600W board rating
  • Datacenter or workstation hardware, not a retail purchase
567.1tok/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
4.45tok/s/W
Most efficient: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
real power sampling, not TDP

What GPU Do You Need for gemma-3-1b?, tok/s by GPU

NVIDIA RTX PRO 6000 Blackwell Workstation Edition
567.1 tok/s
NVIDIA B300
533.3 tok/s
NVIDIA B200
519.2 tok/s
NVIDIA H200
513.6 tok/s
NVIDIA H100 80GB HBM3
504.2 tok/s
NVIDIA L40S
426.5 tok/s
NVIDIA A100 80GB SXM4
324.1 tok/s
NVIDIA A100 40GB SXM4
310.7 tok/s
NVIDIA A10G
284.8 tok/s
NVIDIA L4
216.3 tok/s
NVIDIA T4
156.9 tok/s

Efficiency: tok/s per 100W drawn

NVIDIA RTX PRO 6000 Blackwell Workstation Edition
444.78 tok/s / 100W
NVIDIA L4
436.03 tok/s / 100W
NVIDIA A100 40GB SXM4
352.66 tok/s / 100W
NVIDIA L40S
349.58 tok/s / 100W
NVIDIA H200
336.77 tok/s / 100W
NVIDIA H100 80GB HBM3
331.25 tok/s / 100W
NVIDIA T4
310.04 tok/s / 100W
NVIDIA A10G
293.29 tok/s / 100W
NVIDIA A100 80GB SXM4
252.01 tok/s / 100W
NVIDIA B300
197.09 tok/s / 100W
NVIDIA B200
188.52 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
101.71 tok/s / $1k
NVIDIA L4
86.51 tok/s / $1k
NVIDIA T4
68.24 tok/s / $1k
NVIDIA RTX PRO 6000 Blackwell Workstation Edition
66.21 tok/s / $1k
NVIDIA L40S
56.87 tok/s / $1k
NVIDIA A100 40GB SXM4
25.89 tok/s / $1k
NVIDIA A100 80GB SXM4
19.06 tok/s / $1k
NVIDIA H100 80GB HBM3
16.81 tok/s / $1k
NVIDIA H200
16.57 tok/s / $1k
NVIDIA B300
13.33 tok/s / $1k
NVIDIA B200
12.98 tok/s / $1k

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

gemma-3-1b. Measured tokens per second by GPU

NVIDIA RTX PRO 6000 Blackwell Workstation Edition567.1
NVIDIA B300533.3
NVIDIA B200519.2
NVIDIA H200513.6
NVIDIA H100 80GB HBM3504.2
NVIDIA L40S426.5
NVIDIA A100 80GB SXM4324.1
NVIDIA A100 40GB SXM4310.7
NVIDIA A10G284.8
NVIDIA L4216.3
NVIDIA T4156.9
GPUtok/sPrompt t/stok/WAvg power
NVIDIA RTX PRO 6000 Blackwell Workstation Edition567.135777.54.45127.5 W
NVIDIA B300533.326475.71.97270.6 W
NVIDIA B200519.2325971.89275.4 W
NVIDIA H200513.629193.83.37152.5 W
NVIDIA H100 80GB HBM3504.229130.53.31152.2 W
NVIDIA L40S426.532284.13.5122.0 W
NVIDIA A100 80GB SXM4324.115448.32.52128.6 W
NVIDIA A100 40GB SXM4310.714832.73.5388.1 W
NVIDIA A10G284.816627.22.9397.1 W
NVIDIA L4216.316684.94.3649.6 W
NVIDIA T4156.96464.83.150.6 W

What the numbers show. Across 11 GPUs measured on our own bench, RTX PRO 6000 Blackwell Workstation Edition is fastest at 567 tok/s. The slowest, T4, manages 157, so the spread is 3.6x from top to bottom. Per dollar of launch price, A10G gives the most (101.7 tok/s per $1,000). The fastest card with 16GB or less is T4 at 157 tok/s.

About gemma-3-1b. gemma-3-1b: from google, 1.0B parameters, on Hugging Face since March 2025, Gemma licence (gated: accept the terms first). 3,222,716 downloads in the last 30 days.

How it compares. H100 80GB HBM3: gemma-3-1b 504.2 tok/s, Llama 3.2 1B 880.6 (1B), Qwen3 0.6B 713.5, Qwen2.5-0.5B 890.0, Qwen2 0.5B 881.9. All 4 beat gemma-3-1b here.

Cost on a rented GPU. 1M generated tokens of gemma-3-1b: $0.24 on a T4 ($0.14/hr, 106 min), $0.53 on a RTX PRO 6000 Blackwell Workstation Edition ($1.08/hr, 29 min, 2.2x the cost).

gemma-3-1b: cost per 1M generated tokens on rented GPUs

NVIDIA T4$0.14/hr
NVIDIA A100 40GB SXM4$0.47/hr
NVIDIA L40S$0.79/hr
NVIDIA RTX PRO 6000 Blackwell Workstation Edition$1.08/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/hr156.9$0.24
NVIDIA A100 40GB SXM4$0.47/hr310.7$0.42
NVIDIA L40S$0.79/hr426.5$0.51
NVIDIA RTX PRO 6000 Blackwell Workstation Edition$1.08/hr567.1$0.53
NVIDIA L4$0.44/hr216.3$0.57
NVIDIA A100 80GB SXM4$0.95/hr324.1$0.81
NVIDIA H100 80GB HBM3$2.14/hr504.2$1.18
NVIDIA H200$3.59/hr513.6$1.94
NVIDIA B200$5.98/hr519.2$3.20
NVIDIA B300$6.94/hr533.3$3.61

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

Speed tiers for gemma-3-1b. 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 gemma-3-1b writes anything it reads the input: 35777.5 tok/s on the RTX PRO 6000 Blackwell Workstation Edition (0.1s for a 4,000-token prompt), 6464.8 on the T4 (0.6s). Long documents and big code files feel this number more than the generation speed.

VRAM for gemma-3-1b. Measured peak 1.8GB, so 8GB is the smallest common card size; smallest card it ran on: T4 (16GB). With long context: Q4_K_M 2GB (tested), Q6_K 2GB, Q8_0 2GB.

Power on gemma-3-1b. Most efficient: RTX PRO 6000 Blackwell Workstation Edition, 128W, 62.5 Wh per 1M generated tokens. Hungriest: B200, 275W, 0.15 kWh.

Our verdict

Fastest on gemma-3-1b: NVIDIA RTX PRO 6000 Blackwell Workstation Edition, 567.1 tok/s. Cheapest to rent per job: NVIDIA T4, $0.24 per 1M generated tokens.

FAQ

What GPU do I need to run gemma-3-1b?
About 2GB. Smallest card that ran it: NVIDIA T4 (16GB).
How much does it cost to run gemma-3-1b in the cloud?
$0.24 per 1M generated tokens on a NVIDIA T4 at $0.14/hr, cheapest of 10 rentable cards we measured.
Can I run gemma-3-1b on a 12GB, 16GB or 24GB card?
It used 1.8GB at the precision we tested. 12GB: yes; 16GB: yes; 24GB: yes.
Is the H100 80GB HBM3 or the A100 80GB SXM4 faster for gemma-3-1b?
The H100 80GB HBM3: 504.2 vs 324.1 tok/s, 56% 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.