NVIDIA RTX 4080 Super vs NVIDIA RTX 5050 Laptop
Which graphics card is better for running local language models? Here is how the NVIDIA RTX 4080 Super (16 GB) compares against the NVIDIA RTX 5050 Laptop (8 GB) in real memory headroom, supported model architectures, and generation speed.
NVIDIA · Ada Lovelace
16 GB VRAM
NVIDIA RTX 4080 Super
- Memory Bandwidth: 736 GB/s (GDDR6X 256-bit)
- Fits fully in VRAM: 31 popular models
- Power Draw (TDP): 320W
- Largest recommended (Q4): 20B–22B
NVIDIA · Mobile
8 GB VRAM
NVIDIA RTX 5050 Laptop
- Memory Bandwidth: 256 GB/s (GDDR6)
- Fits fully in VRAM: 25 popular models
- Power Draw (TDP): 150W
- Largest recommended (Q4): 8B
The AI Local Check Verdict: Which GPU should you buy for AI?
The NVIDIA RTX 4080 Super is the clear winner for local AI. It provides both 8 GB more VRAM and higher memory bandwidth (736 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 4080 Super, but NOT on NVIDIA RTX 5050 Laptop
These models run entirely in GPU VRAM on the NVIDIA RTX 4080 Super, but require slow system RAM offload on the NVIDIA RTX 5050 Laptop:
| Model | Size | Downloads | NVIDIA RTX 4080 Super | NVIDIA RTX 5050 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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