NVIDIA GeForce RTX 4060
No editorial image yet — generic vendor mark shown. Credentials in spec table below.
Entry-level Ada. 8GB limits to 7B Q4.
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Sub-scores sum to 398 / 1000. Headline = 398 × 0.70 (Estimated-confidence discount) = 279. 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 272 GB/s bandwidth — 32.6 tok/s estimated. No measured benchmarks yet.
Plain-English: Comfortable for 7B chat.
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.
What it does well
The RTX 4060 is the cheapest Ada-generation consumer card at $299 MSRP / $200-250 used. 8 GB GDDR6 at 272 GB/s + Ada Tensor Cores + FP8 native at the lowest power envelope of any Ada card (115 W TDP). For sub-7B AI workloads + gaming + creator use combined, the 4060 is genuinely the entry-tier pick — fits in any 500 W PSU, runs cool, and CUDA + Ada-gen + FP8 stack works cleanly. Ollama, LM Studio, llama.cpp, single-card vLLM all run.
Where it breaks
- 8 GB ceiling kills serious AI. Same constraint as all 8 GB cards.
- Bandwidth is bottom-tier. 272 GB/s is the lowest of any Ada-gen card and barely above the 8 GB 5060's 448 GB/s. For memory-bound decode, 4060 is meaningfully slower than the 5060.
- Pricing competition is brutal from used market. Used RTX 3060 12GB at $200 has 50% more VRAM at lower price. Used RTX 3070 at $200-300 has same VRAM + more bandwidth + more compute.
- Architecture is one generation behind Blackwell. RTX 5060 at $299 MSRP has FP4 native + slightly more bandwidth at the same price.
- No 16 GB variant in the 4060 SKU class. 4060 is firmly 8 GB.
Ideal model range
- Sweet spot: 7B FP16 / Q5 inference at modest decode speed.
- Sweet spot: Embedding models, classifiers, small re-rankers.
- Sweet spot: First-time AI buyers on tight budget — gaming + AI dual purpose.
- Stretch: 13B Q4 with 4K context.
- Bad fit: 13B+ FP16, 14B+ anything, fine-tuning, longer-context use cases.
Bad use cases
- Anyone targeting 13B+ FP16. Hard 8 GB ceiling.
- Cost-conscious 12 GB seekers. Used RTX 3060 12GB at $200 wins decisively.
- Anyone with $130 more in budget. RTX 4060 Ti 16GB at $429 wins for AI.
- Anyone wanting Blackwell-gen. Pick RTX 5060 at the same MSRP.
Verdict
Buy this if you find a used RTX 4060 at $200-$250, you want gaming + occasional small AI use, and you accept the 8 GB ceiling. RTX 4060 is the cost-floor Ada-gen pick — but Blackwell-gen 5060 at the same MSRP is the architecturally-current alternative.
Skip this if RTX 5060 at $299 MSRP is available (same price, Blackwell + FP4 native), used RTX 3060 12GB at $200 fits (50% more VRAM at lower price), or AI is a real use case (RTX 4060 Ti 16GB at +$130 wins decisively).
How it compares
- vs RTX 5060 → Same VRAM, Ada vs Blackwell. 5060 has FP4 native + slightly more bandwidth at the same MSRP. Pick 5060 for current-gen.
- vs RTX 4060 Ti 8GB → 4060 Ti 8GB has ~25% more compute at +$100 MSRP. Same 8 GB tier.
- vs used RTX 3060 12GB → 50% more VRAM at lower used price. For AI, 3060 12GB wins.
- vs used RTX 3070 (8 GB) → Same VRAM, Ampere vs Ada. 3070 has more bandwidth and compute at similar used pricing. Pick 3070 used for value Ampere; 4060 for new card with FP8 + warranty.
- vs Intel Arc B580 (12 GB) → B580 has 50% more VRAM at -$50 MSRP. Pick B580 for VRAM at price; 4060 for CUDA ecosystem.
Overview
Entry-level Ada. 8GB limits to 7B Q4.
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Specs
| VRAM | 8 GB |
| Power draw (peak) | 115 W |
| Released | 2023 |
| MSRP | $299 |
| Backends | CUDA Vulkan |
Models that fit
Open-weight models small enough to run on NVIDIA GeForce RTX 4060 with usable context.
Frequently asked
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Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.