GPU HEAD-TO-HEAD

NVIDIA RTX 4070 Super vs NVIDIA RTX 3060 Laptop

Which graphics card is better for running local language models? Here is how the NVIDIA RTX 4070 Super (12 GB) compares against the NVIDIA RTX 3060 Laptop (6 GB) in real memory headroom, supported model architectures, and generation speed.

NVIDIA · Ada Lovelace 12 GB VRAM

NVIDIA RTX 4070 Super

  • Memory Bandwidth: 504 GB/s (GDDR6X 192-bit)
  • Fits fully in VRAM: 30 popular models
  • Power Draw (TDP): 220W
  • Largest recommended (Q4): 14B
View all NVIDIA RTX 4070 Super models →
NVIDIA · Mobile 6 GB VRAM

NVIDIA RTX 3060 Laptop

  • Memory Bandwidth: 192 GB/s (GDDR6)
  • Fits fully in VRAM: 22 popular models
  • Power Draw (TDP): 150W
  • Largest recommended (Q4): <4B
View all NVIDIA RTX 3060 Laptop models →

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

The NVIDIA RTX 4070 Super is the clear winner for local AI. It provides both 6 GB more VRAM and higher memory bandwidth (504 GB/s vs 192 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 4070 Super, but NOT on NVIDIA RTX 3060 Laptop

These models run entirely in GPU VRAM on the NVIDIA RTX 4070 Super, but require slow system RAM offload on the NVIDIA RTX 3060 Laptop:

Model Size Downloads NVIDIA RTX 4070 Super NVIDIA RTX 3060 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)
bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF 15.71B 455,099 Fits in VRAM Offload (Slow)
unsloth/Qwen-AgentWorld-35B-A3B-GGUF 34.66B 435,428 Fits in VRAM Offload (Slow)
Qwen/Qwen3-8B-GGUF 8.19B 405,506 Fits in VRAM Offload (Slow)
bartowski/Kwaipilot_KAT-Coder-V2.5-Dev-GGUF 34.66B 397,259 Fits in VRAM Offload (Slow)
MaziyarPanahi/Qwen3-14B-GGUF 14.77B 264,741 Fits in VRAM Offload (Slow)
MaziyarPanahi/Qwen3-30B-A3B-GGUF 30.53B 259,143 Fits in VRAM Offload (Slow)

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