Consumer GPUNVIDIA

NVIDIA GeForce RTX 4060 8GB

Name: NVIDIA GeForce RTX 4060 8GB
Brand: NVIDIA
SKU: rtx-4060
Price: 299 USD
Availability: InStock
Rating: 7.8 (7 reviews)

Curated Aggregate·2024-07-303 workloads · 7 records

MyAI Rating7.8tok/s · Phi-3 Mini

VRAM

8 GB

TDP

115 W

MSRP

$299

Perf/W

0.28 tok/s/W

Cost/1K tok

$0.10/M

Tested

2024-07-30

Quick answer

How fast is NVIDIA GeForce RTX 4060 8GB for local AI workloads?

NVIDIA GeForce RTX 4060 8GB hits 95.0 tok/s on Phi-3 Mini, its strongest benchmarked workload (batch 1, 4096-token context, 8GB VRAM, 115W TDP). It has 7 records across 3 workloads in our database, with a MyAI Rating of 7.8/10. Llama 3 70B Q4 needs ~40GB VRAM, so check the VRAM column before assuming feasibility.

Verdict

NVIDIA GeForce RTX 4060 8GB with 8GB VRAM at 115W TDP, scored across 3 workloads with 7 benchmark records.

Best workload

Phi-3 Mini

95 tok/s

Quantization

Q4_K_M

4K context · batch 1

LLM Inference Performance

Benchmarks (3 workloads)

Workload	Score	Quant	Context	σ	Status	Tested
Llama 3 8B Q4 llm	42.0tok/s	Q4_K_M	2K	,	Curated Aggregate	2024-08-18
Phi-3 Mini llm	95.0tok/s	Q4_K_M	4K	,	Curated Aggregate	2024-06-26
Mistral 7B llm	48.0tok/s	Q4_K_M	2K	,	Curated Aggregate	2024-09-12

MyAI Score

Enthusiast

7.8/10

NVIDIA GeForce RTX 4060 8GB clears a 7.8/10 based on workload-normalized throughput, memory headroom, efficiency, value, trust, and coverage.

Throughput

261

Capability

109

Efficiency

Value

Trust

Coverage

Composite benchmark525 / 1000

Workload Fit

What models fit this 8GB card at different quantization levels.

FP16

7-8B

Excellent

Tight

Won't fit

13-14B

Tight

Won't fit

32B

Won't fit

70B

Won't fit

Top Benchmarks

Phi-3 Mini95 tok/s

Mistral 7B48 tok/s

Llama 3 8B Q442 tok/s

Source

Phi-3 Mini Q4 fits comfortably.

View source How we benchmark →

Public Trust Layer

Trust score

6/10

MyAI rating

7.8

Runs

Freshness

Stale

Source-linked row with explicit verification status.

Tested on 2024-06-26; 792 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 $299 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.

This is a fit-driven buy, not a hype buy. Price discipline matters more than launch excitement here.

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