UNIT · NVIDIA · GPU
4 GB VRAMmobileReviewed November 2026

NVIDIA GeForce RTX 3050 Ti (Mobile)

No editorial image yet — generic vendor mark shown. Credentials in spec table below.

Mobile-only Ampere with 4 GB VRAM at 192 GB/s. The 4 GB ceiling is the bottleneck — 1-3B Q4 only with no headroom for context. CUDA + Tensor cores work, but VRAM keeps the workload tiny. Common in mid-range gaming laptops from 2021-2022; the operator's honest move is to use CPU offload for anything beyond 3B.

Released 2021·192 GB/s memory bandwidth
RUNLOCALAI SCORE
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224/ 1000
DD-tier
Estimated
Throughput
67/ 500
VRAM-fit
30/ 200
Ecosystem
200/ 200
Efficiency
23/ 100

Sub-scores sum to 320 / 1000. Headline = 320 × 0.70 (Estimated-confidence discount) = 224. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →

Extrapolated from 192 GB/s bandwidth — 23.0 tok/s estimated. No measured benchmarks yet.

WORKLOAD FIT
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Plain-English: Doesn't fit modern chat models usefully — vision models won't fit.

7B chat✗
Doesn't fit
14B chat✗
Doesn't fit
32B chat✗
Doesn't fit
70B chat✗
Doesn't fit
Coding agent✗
Doesn't fit
Vision (≤8B VLM)✗
Doesn't fit
Long context (32K)✗
Doesn't fit
✓Comfortable — fits with headroom
~Tight — works, no slack
△Marginal — needs aggressive quant
✗Doesn't fit usefully

Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.

BLK · OVERVIEW

Overview

Mobile-only Ampere with 4 GB VRAM at 192 GB/s. The 4 GB ceiling is the bottleneck — 1-3B Q4 only with no headroom for context. CUDA + Tensor cores work, but VRAM keeps the workload tiny. Common in mid-range gaming laptops from 2021-2022; the operator's honest move is to use CPU offload for anything beyond 3B.

Retailers we'd check:Amazon

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BLK · SPECS

Specs

VRAM4 GB
Power draw (peak)80 W
Released2021
Backends
CUDA
Vulkan

Models that fit

Open-weight models small enough to run on NVIDIA GeForce RTX 3050 Ti (Mobile) with usable context.

all-MiniLM-L6-v2
0.022B · other · fits by VRAM, no benchmark yet
Nomic Embed Text v1.5
0.137B · other · fits by VRAM, no benchmark yet
Kokoro 82M
0.082B · other · fits by VRAM, no benchmark yet
BGE Large EN v1.5
0.335B · other · fits by VRAM, no benchmark yet
Qwen 3 0.6B
0.6B · qwen · fits by VRAM, no benchmark yet
all-mpnet-base-v2
0.109B · other · fits by VRAM, no benchmark yet
XTTS v2
0.46B · other · fits by VRAM, no benchmark yet
BGE Reranker v2 M3
0.57B · other · fits by VRAM, no benchmark yet

Frequently asked

What models can NVIDIA GeForce RTX 3050 Ti (Mobile) run?

With 4GB VRAM, the NVIDIA GeForce RTX 3050 Ti (Mobile) runs small models (3B and under) at modest quantization. See the model list below for tested combinations.

Does NVIDIA GeForce RTX 3050 Ti (Mobile) support CUDA?

Yes — NVIDIA GeForce RTX 3050 Ti (Mobile) is an NVIDIA card with full CUDA support, the most mature local-AI backend. llama.cpp, Ollama, vLLM, and ExLlamaV2 all run natively.

Where next?

Buyer guides
Troubleshooting

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.