What AI models can NVIDIA GeForce RTX 3090 run?

The NVIDIA GeForce RTX 3090 can run 21 AI models. Top performers include Llama 3.2 1B Instruct, Gemma 4 26B-A4B, Arcee Trinity Nano 6B. See the full compatibility table above for speeds and quality ratings.

Is NVIDIA GeForce RTX 3090 good for AI coding?

Yes. With 24 GB, the NVIDIA GeForce RTX 3090 supports the Power AI Coding tier: large coding models at good quality.

How much VRAM does NVIDIA GeForce RTX 3090 have?

The NVIDIA GeForce RTX 3090 has 24 GB of GDDR6X VRAM with 936 GB/s bandwidth.

Can NVIDIA GeForce RTX 3090 run 70B models?

70B models can run on the NVIDIA GeForce RTX 3090 with CPU offloading, but performance will be reduced. Consider a GPU with 48GB+ VRAM for full-speed 70B inference.

Is NVIDIA GeForce RTX 3090 worth it for AI?

At $899, the NVIDIA GeForce RTX 3090 offers 24 GB VRAM and runs 21 AI models. It handles local AI inference well.

Desktop GPU

NVIDIA GeForce RTX 3090

24 GB GDDR6X · 936 GB/s

From

$899

Estimated street price

VRAM

24 GB

Bandwidth

936 GB/s

TDP

350W

Models

Tier

Power

The NVIDIA GeForce RTX 3090 with 24 GB GDDR6X VRAM can handle 21 AI models across chat, coding, ai_coding. Best performance: Llama 3.2 1B Instruct at 220 tok/s (excellent). For AI coding workflows, it supports the Power AI Coding tier, running 32B coding models at good quality. Current price: approximately $899.

Source: OwnRig methodology

VRAM

24 GB

Bandwidth

936 GB/s

Memory Type

GDDR6X

TDP

350W

Form Factor

3-slot, 313mm

Builder Capability: Power AI Coding

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

Software

Inference Backends

The software stacks that matter most for real-world inference on this device.

CUDA

production

Primary high-performance backend for NVIDIA inference workloads.

Vulkan

stable

Fallback backend for llama.cpp and related local runtimes.

What it can run

21 models


Arcee Trinity Mini 26B	Q5_K_M	58 tok/s	Excellent
Arcee Trinity Nano 6B	Q8_0	165 tok/s	Excellent
DeepSeek V3	Q2_K	–	Not viable
Gemma 3 27B	Q4_K_M	18 tok/s	Good
Gemma 4 26B-A4B	Q5_K_M	213 tok/s	Excellent
Gemma 4 31B	Q4_K_M	35 tok/s	Good
Gemma 4 E2B	Q8_0	141 tok/s	Excellent
Gemma 4 E4B	Q8_0	87 tok/s	Excellent
GigaChat Lightning 10B	Q8_0	66 tok/s	Good
Llama 3.1 8B Instruct	Q8_0	70 tok/s	Excellent
Llama 3.2 1B Instruct	Q8_0	220 tok/s	Excellent
Llama 3.2 3B Instruct	Q8_0	150 tok/s	Excellent
NVIDIA Nemotron-3-super-120B-A12B	Q2_K	11 tok/s	Marginal
Phi-4 Mini	Q8_0	140 tok/s	Excellent
Qwen 2.5 Coder 32B Instruct	Q4_K_M	18 tok/s	Good
Qwen3.5-122B-A10B	Q3_K_M	11 tok/s	Marginal
Qwen3.5-27B	Q5_K_M	24 tok/s	Good
Qwen3.5-397B (MoE)	Q2_K	–	Not viable
Qwen3.6-27B	Q5_K_M	24 tok/s	Good
Stable Diffusion 3.5 Large	FP16	–	Excellent
Whisper Large V3 Turbo	FP16	–	Excellent

Showing 21 of 21 entries

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FAQ

Frequently Asked Questions

What AI models can NVIDIA GeForce RTX 3090 run?: The NVIDIA GeForce RTX 3090 can run 21 AI models. Top performers include Llama 3.2 1B Instruct, Gemma 4 26B-A4B, Arcee Trinity Nano 6B. See the full compatibility table above for speeds and quality ratings.
Is NVIDIA GeForce RTX 3090 good for AI coding?: Yes. With 24 GB, the NVIDIA GeForce RTX 3090 supports the Power AI Coding tier: large coding models at good quality.
How much VRAM does NVIDIA GeForce RTX 3090 have?: The NVIDIA GeForce RTX 3090 has 24 GB of GDDR6X VRAM with 936 GB/s bandwidth.
Can NVIDIA GeForce RTX 3090 run 70B models?: 70B models can run on the NVIDIA GeForce RTX 3090 with CPU offloading, but performance will be reduced. Consider a GPU with 48GB+ VRAM for full-speed 70B inference.
Is NVIDIA GeForce RTX 3090 worth it for AI?: At $899, the NVIDIA GeForce RTX 3090 offers 24 GB VRAM and runs 21 AI models. It handles local AI inference well.

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