Can I Run StarCoder 2 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?

Written by Jakub Rusinowski · Last updated February 28, 2024

Yes

Yes — StarCoder 2 7B at Q6_K needs about 7.2 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM) (~0.8 GB spare), at ~30.8 tok/s (estimated), with room for about 16,384 tokens of context.

Confidence: high · Recommended quantization: Q6_K · Estimated speed: ~30.8 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)

StarCoder 2 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM): memory by quantization

QuantMemory neededFits 8 GB?Max contextEst. speedDownload
F1615.7 GB✗ No14.4 GB
Q8_09 GB✗ No7.7 GB
Q6_K7.2 GB✓ Yes16K~30.8 tok/s5.9 GB
Q5_K_M6.4 GB✓ Yes16K~35 tok/s5.1 GB
Q4_K_M5.7 GB✓ Yes16K~40.2 tok/s4.3 GB
Q3_K_M4.4 GB✓ Yes16K~53.7 tok/s3.1 GB
Q2_K3.7 GB✓ Yes16K~65.9 tok/s2.4 GB

Which StarCoder 2 sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
StarCoder 2 15B10.8 GB✗ Too large
StarCoder 2 7B5.7 GB✓ Fits~40.2 tok/s
StarCoder 2 3B2.9 GB✓ Fits~85.2 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 StarCoder 2 on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?

Yes — StarCoder 2 7B at Q6_K needs about 7.2 GB of the 8 GB usable on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM) (~0.8 GB spare), at ~30.8 tok/s (estimated), with room for about 16,384 tokens of context.

Which quantization of StarCoder 2 should I use on RTX 4060 Laptop (8 GB VRAM, 16 GB RAM)?

Q6_K — it needs about 7.2 GB of the 8 GB available, downloads as roughly 5.9 GB, and runs at an estimated 30.8 tokens/sec with up to 16K of context.

What limits StarCoder 2 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)

StarCoder 2 on GPUs

What This Model Is Good At

Model & Tools

← Can I Run It? | StarCoder 2 model page | Check your hardware