NVIDIA GeForce RTX 5090 Laptop GPU — Local LLM Performance & Compatibility
作者： Jakub Rusinowski · 最后更新： 2026年9月19日
256位总线上的24 GB GDDR7，28 Gbps：896 GB/s，而桌面版RTX 5090为32 GB、1792 GB/s。3 GB显存颗粒是笔记本能装下24 GB的原因。按机身设计在95–150 W之间可调，因此同一型号的吞吐量可相差三分之一。
Technical Specifications
| VRAM | 24 GB |
| Memory Bandwidth | 896 GB/s |
| TDP | 150 W |
| Architecture | Blackwell GB203 |
| Release Year | 2025 |
| MSRP at Launch | $0 |
| Inference Speed (Llama 3.1 8B Q4_K_M) | 70–145 tok/s (estimated) |
| Inference Speed (Llama 3.3 70B Q4_K_M) | Does not fit — needs ~44 GB of 24 GB usable |
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LLMs Compatible with 24 GB VRAM
All models below run comfortably in 24 GB VRAM with Q4_K_M quantization.
| Command R Family | Command R (35B) · 22 GB VRAM · Q4_K_M · ollama run command-r |
| Qwen 3.5 | Qwen 3.5 35B-A3B · 22 GB VRAM · Q4_K_M · ollama run qwen3.5:35b-a3b |
| Qwen 3.6 | Qwen 3.6 35B-A3B · 22 GB VRAM · Q4_K_M · ollama run qwen3.6:35b-a3b |
| Nex-N2 | Nex-N2 mini · 22 GB VRAM · Q4_K_M · nex-n2 |
| Yi 1.5 Family | Yi 1.5 34B Chat · 22 GB VRAM · Q4_K_M · ollama run yi:34b |
| Qwen 3 | Qwen 3 32B · 21 GB VRAM · Q4_K_M · ollama run qwen3:32b |
| Aya Expanse | Aya Expanse 32B · 20 GB VRAM · Q4_K_M · ollama run aya-expanse:32b |
| DeepSeek R1 | DeepSeek R1 Distill Qwen 32B · 20 GB VRAM · Q4_K_M · ollama run deepseek-r1:32b |
56 more families also fit 24 GB — browse the full model library.
Best Use Cases
- 24 GB laptop AI
- portable inference
- flagship gaming laptops
FAQ
Can the NVIDIA GeForce RTX 5090 Laptop GPU run local LLMs?
Yes — the NVIDIA GeForce RTX 5090 Laptop GPU has 24 GB VRAM and runs 256位总线上的24 GB GDDR7，28 Gbps：896 GB/s，而桌面版RTX 5090为32 GB、1792 GB/s。3 GB显存颗粒是笔记本能装下24 GB的原因。按机身设计在95–150 W之间可调，因此同一型号的吞吐量可
How fast is the NVIDIA GeForce RTX 5090 Laptop GPU for AI inference?
The NVIDIA GeForce RTX 5090 Laptop GPU is estimated to run Llama 3.1 8B at 70–145 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 24 GB usable. These are modelled estimates, not measurements — see /en/methodology.
What LLMs can I run on 24 GB VRAM?
With 24 GB you can run: Command R Family, Qwen 3.5, Qwen 3.6, Nex-N2, Yi 1.5 Family. Use Ollama for the easiest setup: ollama run llama3.1:8b.
Compare Similar GPUs
- Intel Arc Pro B70 (32 GB, 0 t/s)
- Intel Arc Pro B65 (32 GB, 0 t/s)
- AMD Radeon AI PRO R9700 (32 GB, 0 t/s)
- NVIDIA GeForce RTX 3090 Ti (24 GB, 0 t/s)
VRAM Tier
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