Gemma 3 4B · 11 GPUs measured first-party · llama.cpp Q4_K_M · Updated October 2026
Gemma 3 4B is Google's small open model, a polished generalist with vision support in a ~4GB package. We measured it on 11 GPUs (llama.cpp, Q4_K_M): 301 tok/s on the B300, with the RTX PRO 6000 essentially tied at 298 while drawing 45% less power.
Benchmarked weights: bartowski/google_gemma-3-4b-it-GGUF

301.1 tok/s on Gemma 3 4B, the ceiling. Measured on our bench. 288GB of VRAM, $40,000 at launch.

297.7 tok/s on Gemma 3 4B, lowest launch price that still fits. Measured on our bench. 96GB of VRAM, $8,565 at launch.
What GPU Do You Need for Gemma 3 4B?, tok/s by GPU
Measured on our own bench. A card absent from this chart has not been run on this model yet, or cannot fit it.
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.
Gemma 3 4B. Measured generation speed by GPU
| GPU | tok/s | Prompt t/s | tok/W | Avg power |
|---|---|---|---|---|
| NVIDIA B300 | 301.1 | 9330.5 | 1.06 | 283.1 W |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | 297.7 | 17046.1 | 1.76 | 169.3 W |
| NVIDIA B200 | 291.8 | 14313.1 | 0.88 | 330.8 W |
| NVIDIA H200 | 291.8 | 12728.4 | 1.55 | 188.2 W |
| NVIDIA H100 80GB HBM3 | 289.6 | 13101.8 | 1.37 | 211.0 W |
| NVIDIA L40S | 198.9 | 14777.1 | 1.25 | 159.4 W |
| NVIDIA A100 80GB SXM4 | 176.9 | 7248.6 | 1.45 | 122.2 W |
| NVIDIA A100 40GB SXM4 | 174.1 | 6659.5 | 1.26 | 138.4 W |
| NVIDIA A10G | 124.8 | 5510 | 1.08 | 115.5 W |
| NVIDIA L4 | 82.03 | 5443.2 | 1.37 | 60.0 W |
| NVIDIA T4 | 65.12 | 2317 | 1.08 | 60.4 W |
The Gemma pattern, stated plainly. Our view of the Gemma 3 line: good models that aren't specialized at anything, middle of the pack across the board rather than best-in-class at one thing. At 4B that's actually a defensible profile: you get Google's training polish, clean multilingual behavior and image understanding in one small package. But the small tier is brutal company, Phi-4 Mini answers better, Qwen3 4B has the wider ecosystem, so Gemma 3 4B earns its slot mainly when you specifically want its vision capability or Google's instruction style in a tiny footprint.
Bench behavior. 301 tok/s peak with the usual flat top (the workstation PRO 6000 at 298 tok/s and 1.76 tok/W is the efficiency pick), and a ~4GB floor that any 6GB card clears. A T4 still manages 67 tok/s, comfortably interactive. Hardware is a non-issue for this model; the decision is entirely about which small model's temperament fits your task.
How it compares. H100 80GB HBM3: Gemma 3 4B 289.6 tok/s, Qwen3-30B-A3B 285.4, DeepSeek Coder 7B Instruct v1.5 293.9 (7B), Llama-2-7B 284.6 (7B), Qwen3 30B A3B 283.8 (31B). 1 of 4 beat Gemma 3 4B here.
Cost on a rented GPU. 1M generated tokens of Gemma 3 4B: $0.58 on a T4 ($0.14/hr, 4.3 hours), $6.40 on a B300 ($6.94/hr, 55 min, 11.0x the cost).
Gemma 3 4B: cost per 1M generated tokens on rented GPUs
| GPU | Cheapest rate | Speed (tok/s) | Cost per 1M generated tokens |
|---|---|---|---|
| NVIDIA T4 | $0.14/hr | 65.12 | $0.58 |
| NVIDIA A100 40GB SXM4 | $0.47/hr | 174.1 | $0.75 |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | $1.08/hr | 297.7 | $1.00 |
| NVIDIA L40S | $0.79/hr | 198.9 | $1.10 |
| NVIDIA A100 80GB SXM4 | $0.95/hr | 176.9 | $1.49 |
| NVIDIA L4 | $0.44/hr | 82.03 | $1.49 |
| NVIDIA H100 80GB HBM3 | $2.14/hr | 289.6 | $2.05 |
| NVIDIA H200 | $3.59/hr | 291.8 | $3.42 |
| NVIDIA B200 | $5.98/hr | 291.8 | $5.69 |
| NVIDIA B300 | $6.94/hr | 301.1 | $6.40 |
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 4B. 30+ tok/s: 11 (B300, RTX PRO 6000 Blackwell Workstation Edition, B200). 30 tok/s is roughly where replies outpace reading.
Reading your prompt. Before Gemma 3 4B writes anything it reads the input: 17046.1 tok/s on the RTX PRO 6000 Blackwell Workstation Edition (0.2s for a 4,000-token prompt), 2317.0 on the T4 (1.7s). Long documents and big code files feel this number more than the generation speed.
VRAM for Gemma 3 4B. Measured peak 3.4GB, so 8GB is the smallest common card size; smallest card it ran on: T4 (16GB). With long context: Q4_K_M 4GB (tested), Q2_K 3GB, Q3_K_M 4GB, Q5_K_M 5GB, Q6_K 6GB.
Power on Gemma 3 4B. Most efficient: RTX PRO 6000 Blackwell Workstation Edition, 169W, 0.16 kWh per 1M generated tokens. Hungriest: B200, 331W, 0.31 kWh. At $0.15/kWh: $0.024 per 1M generated tokens.
Gemma 3 4B: 301 tok/s peak, ~4GB floor, vision included, a capable all-rounder in the most competitive weight class we cover. Nothing about it is bad; nothing about it leads. Pick it for the multimodal support or the Google instruction style, not for benchmarks.