Can I Run Cosmos 3 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?

Written by Jakub Rusinowski · Last updated July 21, 2026

Yes — comfortably

Yes, comfortably — Cosmos 3 Edge at Q8_0 needs about 6 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving ~2 GB spare and running at ~67.2 tok/s (estimated), with room for about 16,384 tokens of context.

Confidence: medium · Recommended quantization: Q8_0 · Estimated speed: ~67.2 tok/s

RTX 4060 Laptop (8 GB VRAM, 16 GB RAM) — what it gives a model

Usable memory for models8 GB
Memory bandwidth272 GB/s
Form factorLaptop
Operating systemWindows or Linux
Memory upgradeableYes
Price$1,099 (lib/data/laptops.ts (street price), checked 2026-07-06)

Cosmos 3 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM): memory by quantization

QuantMemory neededFits 8 GB?Max contextEst. speedDownload
F169.7 GB✗ No8 GB
Q8_06 GB✓ Yes16K~67.2 tok/s4.3 GB
Q6_K5 GB✓ Yes16K~80 tok/s3.3 GB
Q5_K_M4.5 GB✓ Yes16K~87.6 tok/s2.8 GB
Q4_K_M4.1 GB✓ Yes16K~96.3 tok/s2.4 GB
Q3_K_M3.4 GB✓ Yes16K~115.7 tok/s1.7 GB
Q2_K3 GB✓ Yes16K~130 tok/s1.3 GB

Which Cosmos 3 sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
Cosmos 3 Super41.8 GB✗ Too large
Cosmos 3 Nano11.9 GB✗ Too large
Cosmos 3 Edge4.1 GB✓ Fits~96.3 tok/s

What to watch out for

RTX 4060 laptop limitations

Recommended setup

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

How these numbers are calculated

FAQ

Can I run Cosmos 3 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?

Yes, comfortably — Cosmos 3 Edge at Q8_0 needs about 6 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM), leaving ~2 GB spare and running at ~67.2 tok/s (estimated), with room for about 16,384 tokens of context.

Which quantization of Cosmos 3 should I use on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?

Q8_0 — it needs about 6 GB of the 8 GB available, downloads as roughly 4.3 GB, and runs at an estimated 67.2 tokens/sec with up to 16K of context.

What limits Cosmos 3 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?

Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.

Which runtime should I use?

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

Other Computers

Other Models on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)

Cosmos 3 on GPUs

What This Model Is Good At

Model & Tools

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