How much VRAM does the NVIDIA RTX 5000 Ada have?

The NVIDIA RTX 5000 Ada has 32 GB of GDDR6 with 576 GB/s memory bandwidth.

What is the NVIDIA RTX 5000 Ada best for?

With 32 GB of VRAM, the NVIDIA RTX 5000 Ada is well-suited for running 7B–32B models at Q4 with room for context, making it a great all-rounder for local LLM inference.

What LLMs can the NVIDIA RTX 5000 Ada run locally?

The NVIDIA RTX 5000 Ada can run 53 of the 94 open-weight models tracked by CanItRun natively in VRAM at 8k context. Top options include: Qwen 3.8 27B at Q6_K, Muse Glimmer 30B at Q6_K, Ornith 1.5 9B at BF16.

Can the NVIDIA RTX 5000 Ada run Gemma 4 31B?

Yes. The NVIDIA RTX 5000 Ada runs Gemma 4 31B natively in VRAM at Q6_K quantization, achieving approximately 14 tokens per second.

Can the NVIDIA RTX 5000 Ada run Qwen 3.6 27B?

Yes. The NVIDIA RTX 5000 Ada runs Qwen 3.6 27B natively in VRAM at Q6_K quantization, achieving approximately 16.5 tokens per second.

Can the NVIDIA RTX 5000 Ada run Qwen3 8B?

Yes. The NVIDIA RTX 5000 Ada runs Qwen3 8B natively in VRAM at BF16 quantization, achieving approximately 21.8 tokens per second.

NVIDIA RTX 5000 Ada

The NVIDIA RTX 5000 Ada has 32 GB VRAM and 576 GB/s memory bandwidth. It can run 53 of our 94 tracked models natively in VRAM at 8k context.

With 32 GB GDDR6, the NVIDIA RTX 5000 Ada is a workstation-tier GPU that can run 53 models natively. It comfortably runs 7B–32B models at Q4; 70B-class models typically need CPU offload.

The NVIDIA RTX 5000 Ada fills the gap between the RTX 4500 Ada and RTX 6000 Ada, featuring 32GB ECC GDDR6 on a 256-bit bus at 576 GB/s with 12,800 CUDA cores. This VRAM headroom enables 34B models at Q4_K_M and most 27B models at Q8_0 to run entirely in memory. Professional ECC memory and certified drivers make it a reliable choice for on-prem AI inference deployments.

NVIDIA RTX 5000 Ada: 2023 Ada Lovelace workstation card bridging the RTX 4500 Ada and RTX 6000 Ada: 32GB ECC GDDR6 on a 256-bit bus at 576 GB/s.

34B models fit at Q4_K_M; most 27B models fit at Q8_0 entirely in VRAM. ~22-30 t/s for 7B Q4.

Full CUDA with ECC and certified drivers. A reliable middle ground for on-prem inference deployments that outgrow 24GB but don't need the RTX 6000 Ada's 48GB.

Vendor	NVIDIA
Architecture	Ada Lovelace
VRAM	32 GB
Memory type	GDDR6
Memory bandwidth	576 GB/s
Compute backend	CUDA
Tier	Workstation
Released	2023
Models (native)	53 / 94
Models (offload)	9 / 94

Software: Full llama.cpp and Ollama support out of the box. CUDA 12.x recommended; driver ≥ 525 required.

Popular models for this GPU

Mixtral 8x7B Instruct v0.1 Command-R 35B Qwen 3.5 35B-A3B (MoE)Qwen 3.6 35B Ornith 1.5 35B-A3B (MoE)

Models this GPU runs natively in VRAM (53)

Show 48 more

Models that fit with CPU offload (9)

These use system RAM for layers that don't fit in VRAM, so expect much slower inference.

Too large for this GPU (32)

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Frequently asked questions

How much VRAM does the NVIDIA RTX 5000 Ada have?: The NVIDIA RTX 5000 Ada has 32 GB of GDDR6 with 576 GB/s memory bandwidth.
What is the NVIDIA RTX 5000 Ada best for?: With 32 GB of VRAM, the NVIDIA RTX 5000 Ada is well-suited for running 7B–32B models at Q4 with room for context, making it a great all-rounder for local LLM inference.
What LLMs can the NVIDIA RTX 5000 Ada run locally?: The NVIDIA RTX 5000 Ada can run 53 of the 94 open-weight models tracked by CanItRun natively in VRAM at 8k context. Top options include: Qwen 3.8 27B at Q6_K, Muse Glimmer 30B at Q6_K, Ornith 1.5 9B at BF16.
Can the NVIDIA RTX 5000 Ada run Gemma 4 31B?: Yes. The NVIDIA RTX 5000 Ada runs Gemma 4 31B natively in VRAM at Q6_K quantization, achieving approximately 14 tokens per second.
Can the NVIDIA RTX 5000 Ada run Qwen 3.6 27B?: Yes. The NVIDIA RTX 5000 Ada runs Qwen 3.6 27B natively in VRAM at Q6_K quantization, achieving approximately 16.5 tokens per second.
Can the NVIDIA RTX 5000 Ada run Qwen3 8B?: Yes. The NVIDIA RTX 5000 Ada runs Qwen3 8B natively in VRAM at BF16 quantization, achieving approximately 21.8 tokens per second.