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⇱ Can SmolLM3 3B Run on NVIDIA L20 48GB? YES (9.5/48.0GB)


Can SmolLM3 3B run on NVIDIA L20 48GB?

YES — Runs Great

C52Usable
Estimated from fit model

SmolLM3 3B needs ~9.5 GB VRAM. NVIDIA L20 48GB has 48.0 GB. With Q4_K_M quantization, expect ~48 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
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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) — 9.5 GB, 48.0 tok/s, Runs well
9.5 GB required48.0 GB available
20% VRAM used

Fit status

Runs well

Decode

48.0 tok/s

TTFT

4033 ms

Safe context

128K

Memory

9.5 GB / 48.0 GB

Memory breakdown

Weights1.8 GB
KV Cache2.0 GB
Runtime0.9 GB
Headroom4.8 GB

See how fast it feels

See how fast it feelsSmolLM3 3B on NVIDIA L20 48GB
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: 48.0 tok/s decode · 4.0s TTFT (warm) · 120 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

WorkloadGradeFitDecodeTTFTContext
ChatCRuns well48.0 tok/s2200 ms128K
CodingCRuns well48.0 tok/s4033 ms128K
Agentic CodingCRuns well48.0 tok/s5867 ms128K
ReasoningCRuns well48.0 tok/s4767 ms128K
RAGCRuns well48.0 tok/s7333 ms128K

Quantization options

How SmolLM3 3B (3B params) fits at each quantization level on NVIDIA L20 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
1.2 GB
LowC49
Q3_K_S
3
1.5 GB
LowC49
NVFP4
4
1.7 GB
MediumC49
Q4_K_M
4
1.8 GB
MediumC49
Q5_K_M
5
2.2 GB
HighC49
Q6_K
6
2.5 GB
HighC49
Q8_0
8
3.2 GB
Very HighC49
F16Best for your GPU
16
6.1 GB
MaximumC50

Get started

Copy-paste commands to run SmolLM3 3B on your machine.

Run

lms load SmolLM3-3B && lms server start

Upgrade options

Hardware that runs SmolLM3 3B well

MacBook Pro M4 Max 96GBBudget pick
96 GB Unified (+48)
C
Adds memory headroom for longer context windows and future model growth.42 tok/s decode

Adds memory headroom for longer context windows and future model growth.

~$2,499 MSRP

MacBook Pro M2 Max 96GBBest value
96 GB Unified (+48)
C
Adds memory headroom for longer context windows and future model growth.42 tok/s decode

Adds memory headroom for longer context windows and future model growth.

~$3,199 MSRP

Frequently asked questions

See all results for NVIDIA L20 48GBSee all hardware for SmolLM3 3B