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RTX 4060 vs RTX 5060 – Same 8GB, Different Silicon

Two 8GB cards that look interchangeable on a spec sheet - until you look at bandwidth, FP8, and what AI workloads actually care about.

Both the RTX 4060 and the RTX 5060 Blackwell ship with 8 GB of VRAM. On our dedicated hosting they occupy the same tier. That is where the similarity ends. The newer card is a different class of silicon sharing a VRAM capacity, not a marginally faster version of the old one.

Contents

Specs

SpecRTX 4060RTX 5060 Blackwell
VRAM8 GB GDDR68 GB GDDR7
Bandwidth~272 GB/s~448 GB/s
FP8 tensorNoYes
FP16 TFLOPS~242~330+
TDP115 W150 W

Bandwidth Matters

GDDR7 on the 5060 is nearly double the effective bandwidth of the 4060’s GDDR6. For LLM decode that is a near-direct speed ratio. Mistral 7B at INT4 on the 4060 hits maybe 25 tokens/sec; the 5060 crosses 40 under the same conditions. If decode speed is your headline metric – user waits for text – the 5060 feels materially faster. See the lineup bandwidth ranking for the full picture.

FP8 Support

This is the under-appreciated Blackwell feature. Models increasingly ship with FP8 checkpoints – they are smaller than FP16 and run on tensor cores designed for them. A Mistral 7B FP8 model fits in roughly 7 GB, barely squeaks into the 4060 but with no KV cache room. The 5060 runs the same checkpoint with real headroom and executes it on native FP8 kernels. The 4060 has to convert on load – you lose the speed advantage. Over the next 18 months more published checkpoints will be FP8.

Real Workloads

WorkloadRTX 4060RTX 5060
Phi-3-mini INT4~60 t/s~95 t/s
Mistral 7B INT4~25 t/s~42 t/s
Llama 3 8B INT4~18 t/s, short ctx~32 t/s, short ctx
SDXL 1024 base 30 steps~8 s~5 s
Whisper large v3Works, slowWorks with margin

Budget Entry Without Regret

Fixed monthly UK hosting on either card – we provision same-day.

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Which to Pick

Pick the 4060 when your budget is rigid and your workload is a stable quantised 3-7B model with undemanding latency. Pick the 5060 when your budget can stretch slightly, FP8 models are on your roadmap, or you want the card to stay relevant for the next two years. The price delta is usually small and the capability delta is not. For the next step up, see 4060 Ti vs 5060 – if you can afford the jump to 16 GB, it is almost always the better move.

Also see Blackwell vs Ada generational leap for architecture-level context.

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We benchmark, deploy, and optimise GPU infrastructure for AI workloads. All data in our guides comes from real-world testing on our UK-based dedicated GPU servers.

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