GPU HEAD-TO-HEAD

NVIDIA RTX 5080 vs NVIDIA RTX 4060 Laptop

Which graphics card is better for running local language models? Here is how the NVIDIA RTX 5080 (16 GB) compares against the NVIDIA RTX 4060 Laptop (8 GB) in real memory headroom, supported model architectures, and generation speed.

NVIDIA · Blackwell 16 GB VRAM

NVIDIA RTX 5080

  • Memory Bandwidth: 960 GB/s (GDDR7 256-bit)
  • Fits fully in VRAM: 31 popular models
  • Power Draw (TDP): 400W
  • Largest recommended (Q4): 20B–22B
View all NVIDIA RTX 5080 models →
NVIDIA · Mobile 8 GB VRAM

NVIDIA RTX 4060 Laptop

  • Memory Bandwidth: 256 GB/s (GDDR6)
  • Fits fully in VRAM: 25 popular models
  • Power Draw (TDP): 150W
  • Largest recommended (Q4): 8B
View all NVIDIA RTX 4060 Laptop models →

The AI Local Check Verdict: Which GPU should you buy for AI?

The NVIDIA RTX 5080 is the clear winner for local AI. It provides both 8 GB more VRAM and higher memory bandwidth (960 GB/s vs 256 GB/s).

This allows it to run larger model architectures entirely in video memory while also delivering faster token generation speeds on models of all sizes.

Models that fit on NVIDIA RTX 5080, but NOT on NVIDIA RTX 4060 Laptop

These models run entirely in GPU VRAM on the NVIDIA RTX 5080, but require slow system RAM offload on the NVIDIA RTX 4060 Laptop:

Model Size Downloads NVIDIA RTX 5080 NVIDIA RTX 4060 Laptop
unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF 30.53B 12,866,779 Fits in VRAM Offload (Slow)
unsloth/gpt-oss-20b-GGUF 20.91B 544,532 Fits in VRAM Offload (Slow)
unsloth/Qwen-AgentWorld-35B-A3B-GGUF 34.66B 435,428 Fits in VRAM Offload (Slow)
bartowski/Kwaipilot_KAT-Coder-V2.5-Dev-GGUF 34.66B 397,259 Fits in VRAM Offload (Slow)
MaziyarPanahi/Qwen3-30B-A3B-GGUF 30.53B 259,143 Fits in VRAM Offload (Slow)
MaziyarPanahi/Qwen3-32B-GGUF 32.76B 259,026 Fits in VRAM Offload (Slow)

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