NVIDIA

NVIDIA GeForce RTX 5090

Name: NVIDIA GeForce RTX 5090
Brand: NVIDIA
Price: 2199 USD
Availability: InStock

32 GB · 1792 GB/s

$2,199

Updated 2026-03-01

The NVIDIA GeForce RTX 5090 with 32 GB GDDR7 VRAM can handle 15 AI models across chat, coding, ai_coding. Best performance: Llama 3.2 1B Instruct at 300 tok/s (excellent). For AI coding workflows, it supports the Power AI Coding tier — runs 32B coding models at good quality. Current price: approximately $2,199.

— OwnRig methodology, data updated 2026-03-01

Builder Capability: Power AI Coding

Runs 32B coding models at good quality. Can handle coding model + embeddings concurrently.

Specifications

Memory

Capacity: 32 GB
Bandwidth: 1792 GB/s
Type: GDDR7

Power & Form Factor

TDP: 575W
Rec. PSU: 1000W
Slots: 3-slot
Length: 340mm

Compatible Models

Model	Quant	Speed	Rating	Notes
Llama 3.1 8B Instruct	Q8_0	170 tok/s	Excellent	RTX 5090 bandwidth (1792 GB/s) ~1.8x 4090. Near-instant 8B inference.
Llama 3.1 70B Instruct	Q4_K_M	14 tok/s	Good	32GB VRAM fits 70B Q4. 5090 bandwidth makes it usable without offloading.
Qwen 2.5 Coder 32B Instruct	Q5_K_M	45 tok/s	Excellent	Q5 at ~22GB. 5090 bandwidth delivers excellent coding speed.
DeepSeek R1 Distill Qwen 32B	Q5_K_M	42 tok/s	Excellent	Q5 32B reasoning fits on 32GB. Best local reasoning performance.
Llama 3.3 70B Instruct	Q4_K_M	12 tok/s	Good	70B Q4 fits on 32GB 5090. Usable without offloading.
Mistral Small 24B Instruct	Q5_K_M	55 tok/s	Excellent	24B Q5 benefits from 5090 bandwidth. Excellent general-purpose speed.
Stable Diffusion XL 1.0	FP16	—	Excellent	~2-3 seconds per 1024x1024 image. Massive headroom for LoRA stacking.
Stable Diffusion 3 Medium	FP16	—	Excellent	Full FP16 SD3 Medium. ~5-7 seconds per image. Best quality.
Llama 3.2 3B Instruct	Q8_0	200 tok/s	Excellent	1792 GB/s bandwidth. Maximum possible 3B speed.
Llama 3.2 1B Instruct	Q8_0	300 tok/s	Excellent	1792 GB/s. Maximum possible 1B inference speed.
Phi-4 Mini	Q8_0	185 tok/s	Excellent	1792 GB/s. Maximum Phi-4 mini speed.
Whisper Large V3 Turbo	FP16	—	Excellent	1792 GB/s. Minimum transcription latency.
Stable Diffusion 3.5 Large	FP16	—	Excellent	1792 GB/s. 32GB fits FP16 with 19GB headroom. ~2.5s per image. Fastest SD 3.5 Large.
Gemma 3 27B	Q5_K_M	35 tok/s	Excellent	32GB allows Q5_K_M with 12.7GB headroom. 1792 GB/s bandwidth delivers excellent throughput.
DeepSeek V3	Q2_K	—	Not Viable	671B MoE model requires 115GB+ at Q2_K. 32GB insufficient. Would need 128GB+ unified memory.

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Frequently Asked Questions

What AI models can NVIDIA GeForce RTX 5090 run?: The NVIDIA GeForce RTX 5090 can run 15 AI models. Top performers include Llama 3.2 1B Instruct, Llama 3.2 3B Instruct, Phi-4 Mini. See the full compatibility table above for speeds and quality ratings.
Is NVIDIA GeForce RTX 5090 good for AI coding?: Yes. With 32 GB, the NVIDIA GeForce RTX 5090 supports the Power AI Coding tier — large coding models at good quality.
How much VRAM does NVIDIA GeForce RTX 5090 have?: The NVIDIA GeForce RTX 5090 has 32 GB of GDDR7 VRAM with 1792 GB/s bandwidth.
Can NVIDIA GeForce RTX 5090 run 70B models?: Yes. The NVIDIA GeForce RTX 5090 can run 70B parameter models in VRAM at quantized quality.
Is NVIDIA GeForce RTX 5090 worth it for AI?: At $2,199, the NVIDIA GeForce RTX 5090 offers 32 GB VRAM and runs 15 AI models. It's a strong choice for local AI inference.

Generation: Blackwell. Last updated: 2026-03-01.

Compatible Models

Model	Quant	Speed	Rating	Notes
Llama 3.1 8B Instruct	Q8_0	170 tok/s	Excellent	RTX 5090 bandwidth (1792 GB/s) ~1.8x 4090. Near-instant 8B inference.
Llama 3.1 70B Instruct	Q4_K_M	14 tok/s	Good	32GB VRAM fits 70B Q4. 5090 bandwidth makes it usable without offloading.
Qwen 2.5 Coder 32B Instruct	Q5_K_M	45 tok/s	Excellent	Q5 at ~22GB. 5090 bandwidth delivers excellent coding speed.
DeepSeek R1 Distill Qwen 32B	Q5_K_M	42 tok/s	Excellent	Q5 32B reasoning fits on 32GB. Best local reasoning performance.
Llama 3.3 70B Instruct	Q4_K_M	12 tok/s	Good	70B Q4 fits on 32GB 5090. Usable without offloading.
Mistral Small 24B Instruct	Q5_K_M	55 tok/s	Excellent	24B Q5 benefits from 5090 bandwidth. Excellent general-purpose speed.
Stable Diffusion XL 1.0	FP16	—	Excellent	~2-3 seconds per 1024x1024 image. Massive headroom for LoRA stacking.
Stable Diffusion 3 Medium	FP16	—	Excellent	Full FP16 SD3 Medium. ~5-7 seconds per image. Best quality.
Llama 3.2 3B Instruct	Q8_0	200 tok/s	Excellent	1792 GB/s bandwidth. Maximum possible 3B speed.
Llama 3.2 1B Instruct	Q8_0	300 tok/s	Excellent	1792 GB/s. Maximum possible 1B inference speed.
Phi-4 Mini	Q8_0	185 tok/s	Excellent	1792 GB/s. Maximum Phi-4 mini speed.
Whisper Large V3 Turbo	FP16	—	Excellent	1792 GB/s. Minimum transcription latency.
Stable Diffusion 3.5 Large	FP16	—	Excellent	1792 GB/s. 32GB fits FP16 with 19GB headroom. ~2.5s per image. Fastest SD 3.5 Large.
Gemma 3 27B	Q5_K_M	35 tok/s	Excellent	32GB allows Q5_K_M with 12.7GB headroom. 1792 GB/s bandwidth delivers excellent throughput.
DeepSeek V3	Q2_K	—	Not Viable	671B MoE model requires 115GB+ at Q2_K. 32GB insufficient. Would need 128GB+ unified memory.

Frequently Asked Questions

What AI models can NVIDIA GeForce RTX 5090 run?

The NVIDIA GeForce RTX 5090 can run 15 AI models. Top performers include Llama 3.2 1B Instruct, Llama 3.2 3B Instruct, Phi-4 Mini. See the full compatibility table above for speeds and quality ratings.

Is NVIDIA GeForce RTX 5090 good for AI coding?

Yes. With 32 GB, the NVIDIA GeForce RTX 5090 supports the Power AI Coding tier — large coding models at good quality.

How much VRAM does NVIDIA GeForce RTX 5090 have?

The NVIDIA GeForce RTX 5090 has 32 GB of GDDR7 VRAM with 1792 GB/s bandwidth.

Can NVIDIA GeForce RTX 5090 run 70B models?

Yes. The NVIDIA GeForce RTX 5090 can run 70B parameter models in VRAM at quantized quality.

Is NVIDIA GeForce RTX 5090 worth it for AI?

At $2,199, the NVIDIA GeForce RTX 5090 offers 32 GB VRAM and runs 15 AI models. It's a strong choice for local AI inference.