Can Gemma 3 4B run on RTX 4060 Ti 16GB?

YES — Runs Great

A71Great

Estimated from fit model

Gemma 3 4B needs ~7.3 GB VRAM. RTX 4060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~56 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: Balanced

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 7.3 GB, 56.0 tok/s, Runs well

7.3 GB required16.0 GB available

46% VRAM used

Fit status

Runs well

Decode

56.0 tok/s

TTFT

3457 ms

Safe context

83K

Memory

7.3 GB / 16.0 GB

Memory breakdown

Weights2.4 GB

KV Cache2.1 GB

Runtime1.2 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsGemma 3 4B on RTX 4060 Ti 16GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.

Given information:
  - Speed = 60 mph (miles per hour)
  - Time  = 2.5 hours

Formula: Distance = Speed x Time

Calculation:
  Distance = 60 mph x 2.5 h
           = 150 miles

The train travels 150 miles.

Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.

Breakdown:
  - First half: 1.25 hours at 60 mph = 75 miles
  - Stop: 20 minutes (no distance)
  - Second half: 1.25 hours at 60 mph = 75 miles

Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph

The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 56.0 tok/s decode · 3.5s TTFT (warm) · 140 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	B	Runs well	56.0 tok/s	1886 ms	83K
Coding	A	Runs well	56.0 tok/s	3457 ms	83K
Agentic Coding	A	Runs well	56.0 tok/s	5029 ms	83K
Reasoning	A	Runs well	56.0 tok/s	4086 ms	83K
RAG	A	Runs well	56.0 tok/s	6286 ms	83K

Inference speed

Gemma 3 4B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Gemma 3 4B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~76 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / Mac	Memory	Quant	Speed (tok/s)	Fits?
RTX 5090 32GB	32 GB	Q4_K_M	76.0	Fits
RTX 4090 24GB	24 GB	Q4_K_M	64.0	Fits
RTX 4080 Super 16GB	16 GB	Q4_K_M	64.0	Fits
RTX 4060 8GB	8 GB	Q4_K_M	57.2	Fits
RTX 3090 24GB	24 GB	Q4_K_M	56.0	Fits
RTX 4070 12GB	12 GB	Q4_K_M	56.0	Fits
RTX 3060 12GB	12 GB	Q4_K_M	56.0	Fits
RX 7900 XTX 24GB	24 GB	Q4_K_M	56.0	Fits
MacBook Pro M4 Max 128GB	128 GB	Q4_K_M	56.0	Fits
Mac Studio M3 Ultra 256GB	256 GB	Q4_K_M	56.0	Fits
Mac Studio M2 Ultra 128GB	128 GB	Q4_K_M	56.0	Fits
Mac Studio M1 Ultra 128GB	128 GB	Q4_K_M	56.0	Fits
MacBook Pro M4 Max 64GB	64 GB	Q4_K_M	56.0	Fits
MacBook Pro M3 Max 64GB	64 GB	Q4_K_M	56.0	Fits
MacBook Pro M1 Max 64GB	64 GB	Q4_K_M	56.0	Fits
MacBook Pro M4 Pro 48GB	48 GB	Q4_K_M	56.0	Fits

Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.

Quantization options

How Gemma 3 4B (4B params) fits at each quantization level on RTX 4060 Ti 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	1.6 GB	Low	B67
Q3_K_S	3	2.0 GB	Low	B67
NVFP4	4	2.2 GB	Medium	B68
Q4_K_M	4	2.4 GB	Medium	B68
Q5_K_M	5	2.9 GB	High	B68
Q6_K	6	3.3 GB	High	B68
Q8_0	8	4.3 GB	Very High	B69
F16Best for your GPU	16	8.2 GB	Maximum	A73

Get started

Copy-paste commands to run Gemma 3 4B on your machine.

Run

ollama run gemma3:4b

Your hardware

More models your RTX 4060 Ti 16GB can run

Model	Params	Grade	Decode
Qwen 3.5 9B	9B	S	41.2 tok/s
Qwen 3 14B	14B	S	26.6 tok/s
Qwen 3 8B	8B	S	46.3 tok/s
Phi-4-reasoning-plus 14B	14.7B	S	25.2 tok/s
GPT-OSS 20B	21B	A	23.5 tok/s

Frequently asked questions

Can RTX 4060 Ti 16GB run Gemma 3 4B?

Yes, RTX 4060 Ti 16GB can run Gemma 3 4B with a A grade (Runs well). Expected decode speed: 56.0 tok/s.

How much VRAM does Gemma 3 4B need?

Gemma 3 4B (4B parameters) requires approximately 7.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Gemma 3 4B?

The recommended quantization for Gemma 3 4B is Q4_K_M, which balances quality and memory efficiency.

What speed will Gemma 3 4B run at on RTX 4060 Ti 16GB?

On RTX 4060 Ti 16GB, Gemma 3 4B achieves approximately 56.0 tokens per second decode speed with a time-to-first-token of 3457ms using Q4_K_M quantization.

Can RTX 4060 Ti 16GB run Gemma 3 4B for coding?

For coding workloads, Gemma 3 4B on RTX 4060 Ti 16GB receives a A grade with 56.0 tok/s and 83K context.

What context window can Gemma 3 4B use on RTX 4060 Ti 16GB?

On RTX 4060 Ti 16GB, Gemma 3 4B can safely use up to 83K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for RTX 4060 Ti 16GB See all hardware for Gemma 3 4B

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Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

56.0 tok/s

1886 ms

83K

Coding

Runs well

56.0 tok/s

3457 ms

83K

Agentic Coding

Runs well

56.0 tok/s

5029 ms

83K

Reasoning

Runs well

56.0 tok/s

4086 ms

83K

RAG

Runs well

56.0 tok/s

6286 ms

83K

Gemma 3 4B inference speed — tokens per second by GPU & Mac

GPU / Mac

Memory

Quant

Speed (tok/s)

Fits?

RTX 5090 32GB

32 GB

Q4_K_M

76.0

Fits

RTX 4090 24GB

24 GB

Q4_K_M

64.0

Fits

RTX 4080 Super 16GB

16 GB

Q4_K_M

64.0

Fits

RTX 4060 8GB

8 GB

Q4_K_M

57.2

Fits

RTX 3090 24GB

24 GB

Q4_K_M

56.0

Fits

RTX 4070 12GB

12 GB

Q4_K_M

56.0

Fits

RTX 3060 12GB

12 GB

Q4_K_M

56.0

Fits

RX 7900 XTX 24GB

24 GB

Q4_K_M

56.0

Fits

MacBook Pro M4 Max 128GB

128 GB

Q4_K_M

56.0

Fits

Mac Studio M3 Ultra 256GB

256 GB

Q4_K_M

56.0

Fits

Mac Studio M2 Ultra 128GB

128 GB

Q4_K_M

56.0

Fits

Mac Studio M1 Ultra 128GB

128 GB

Q4_K_M

56.0

Fits

MacBook Pro M4 Max 64GB

64 GB

Q4_K_M

56.0

Fits

MacBook Pro M3 Max 64GB

64 GB

Q4_K_M

56.0

Fits

MacBook Pro M1 Max 64GB

64 GB

Q4_K_M

56.0

Fits

MacBook Pro M4 Pro 48GB

48 GB

Q4_K_M

56.0

Fits

Quant

Bits

VRAM

Quality

Fit

Q2_K

1.6 GB

Low

B67

Q3_K_S

2.0 GB

Low

B67

NVFP4

2.2 GB

Medium

B68

Q4_K_M

2.4 GB

Medium

B68

Q5_K_M

2.9 GB

High

B68

Q6_K

3.3 GB

High

B68

Q8_0

4.3 GB

Very High

B69

F16Best for your GPU

8.2 GB

Maximum

A73

Model

Params

Grade

Decode

Capabilities

Qwen 3.5 9B

41.2 tok/s

Qwen 3 14B

14B

26.6 tok/s

Qwen 3 8B

46.3 tok/s

Phi-4-reasoning-plus 14B

14.7B

25.2 tok/s

GPT-OSS 20B

21B

23.5 tok/s

Frequently asked questions

Can RTX 4060 Ti 16GB run Gemma 3 4B?

Yes, RTX 4060 Ti 16GB can run Gemma 3 4B with a A grade (Runs well). Expected decode speed: 56.0 tok/s.

How much VRAM does Gemma 3 4B need?

Gemma 3 4B (4B parameters) requires approximately 7.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Gemma 3 4B?

The recommended quantization for Gemma 3 4B is Q4_K_M, which balances quality and memory efficiency.

What speed will Gemma 3 4B run at on RTX 4060 Ti 16GB?

On RTX 4060 Ti 16GB, Gemma 3 4B achieves approximately 56.0 tokens per second decode speed with a time-to-first-token of 3457ms using Q4_K_M quantization.

Can RTX 4060 Ti 16GB run Gemma 3 4B for coding?

For coding workloads, Gemma 3 4B on RTX 4060 Ti 16GB receives a A grade with 56.0 tok/s and 83K context.

What context window can Gemma 3 4B use on RTX 4060 Ti 16GB?

On RTX 4060 Ti 16GB, Gemma 3 4B can safely use up to 83K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.