Consumer GPUNVIDIA

NVIDIA GeForce RTX 3060 12GB

Curated Aggregate·2025-12-115 workloads · 6 records
MyAI RatingNot scoredInsufficient comparison evidence

VRAM

12 GB

TDP

170 W

MSRP

$329

Perf/W

0.25 tok/s/W

Cost/1K tok

$0.08/M

Tested

2025-12-11

Quick answer

How fast is NVIDIA GeForce RTX 3060 12GB for local AI workloads?

NVIDIA GeForce RTX 3060 12GB has a source-attributed result of 42.0 tok/s on Llama 3 8B Q4 (batch 1, 4096-token context, Q4_K_M; runtime not documented). This is a reference report, not an independently verified lab result. A 70B Q4_K_M artifact needs roughly 40GB for weights alone; smaller memory configurations require explicit offload or model splitting and do not establish full-GPU residency.

Source: MyAIHardware benchmark database (bench-rtx3060-l3-8b-q4)As of 2025-12-11

Overview

Budget Entry

NVIDIA GeForce RTX 3060 12GB — Ampere budget card. 12GB GDDR6 at 360 GB/s, 170W TDP. Surprisingly more VRAM than the 3060 Ti/3070/3070 Ti (all 8GB).

AI Usefulness

The cheapest 12GB card with CUDA support. Runs 7B Q4 comfortably, 13B Q4 with tight context. ~20-28 tok/s on 12B models. The minimum viable CUDA card for local AI experimentation. Excellent for learning, small coding agents, and embedding generation. Avoid if you need 13B+ models with real context windows.

Verdict

NVIDIA GeForce RTX 3060 12GB with 12GB VRAM at 170W TDP, scored across 5 workloads with 6 benchmark records.

Reference workload

Llama 3 8B Q4

42 tok/s

Quantization

Q4_K_M

4K context · batch 1

LLM Inference Performance

0255075100Llama 3 8BQ4Mistral 7BPhi-3 MiniGemma 29BAsure 12B

Benchmarks (5 workloads)

WorkloadScoreQuantContextσStatusTested
Llama 3 8B Q4

llm

42.0tok/sQ4_K_M4K, Curated Aggregate2025-12-11
Mistral 7B

llm

48.0tok/sQ4_K_M4K, Curated Aggregate2025-06-02
Phi-3 Mini

llm

92.0tok/sQ4_K_M4K, Curated Aggregate2024-06-01
Gemma 2 9B

llm

32.0tok/sQ4_K_M8K, Curated Aggregate2024-06-04
Asure 12B

llm

28.0tok/sQ4_K_M8K, Curated Aggregate2025-05-01

MyAI Score: not scored

There is insufficient comparable evidence to score NVIDIA GeForce RTX 3060 12GB. A score needs results for multiple devices with matching workload, runtime version, quantization, context and batch size.

Workload Fit

Planning estimates for 12GB: weights plus at least 2GB or 10% overhead. Actual KV cache depends on model, context and cache format; confirm the artifact before buying.

Q4
Q8
FP16
7-8B
Excellent
Good
Won't fit
13-14B
Good
Won't fit
Won't fit
32B
Won't fit
Won't fit
Won't fit
70B
Won't fit
Won't fit
Won't fit
Reported batch-one examples
Llama 3 8B Q442 tok/s
Mistral 7B48 tok/s
Asure 12B28 tok/s

Source

Community-submitted — best $/tok·s in the lineup.

View sourceHow we benchmark →

Public Trust Layer

Trust score

6/10

MyAI rating

Not scored

Runs

Not documented

Freshness

Stale

Source-linked row with explicit verification status.

Record date: 2025-12-11; 272 days old.

Open primary source

Best place to start

Where to buy

Search first

Retailer we'd check first

Amazon search

For mainstream AI hardware, Amazon usually updates street pricing, seller availability, and shipping speed faster than most comparison sites.

Search Amazon listings
  • +Use $329 as your price anchor unless the part is clearly supply-constrained or newly launched.
  • +Check the exact cooler, board partner, or memory configuration before buying. The silicon may match, but noise and thermals do not.
  • +If the Amazon price looks inflated, wait or compare against recent street pricing rather than paying a panic premium.

There is insufficient comparable evidence for a purchase recommendation. Check model fit, software support and a current seller quote.

Affiliate note: we do not have a device-level ASIN yet, so this opens tagged Amazon search results for the exact product name.