NVIDIA

NVIDIA GeForce RTX 3060 12GB

Name: NVIDIA GeForce RTX 3060 12GB
Brand: NVIDIA
Price: 269 USD
Availability: InStock

12 GB · 360 GB/s

$269

Updated 2026-03-01

The NVIDIA GeForce RTX 3060 12GB with 12 GB GDDR6 VRAM can handle 22 AI models across chat, coding, ai_coding. Best performance: Llama 3.2 1B Instruct at 140 tok/s (excellent). For AI coding workflows, it supports the Starter AI Coding tier — good for 7-8B models. Current price: approximately $269.

— OwnRig methodology, data updated 2026-03-01

Builder Capability: Starter AI Coding

Runs 7-8B models comfortably. Good for basic local code completion and small model experiments.

Specifications

Memory

Capacity: 12 GB
Bandwidth: 360 GB/s
Type: GDDR6

Power & Form Factor

TDP: 170W
Rec. PSU: 550W
Slots: 2-slot
Length: 242mm

Compatible Models

Model	Quant	Speed	Rating	Notes
Llama 3.1 8B Instruct	Q5_K_M	35 tok/s	Good	Comfortable fit with 6.2GB headroom. Good speed despite lower bandwidth.
DeepSeek Coder V2 Lite 16B	Q4_K_M	40 tok/s	Good	MoE architecture — only 2.4B active params per token. Speed closer to a 3B model despite 15.7B total. Fits at Q4 (9.1GB) with headroom.
nomic-embed-text v1.5	FP16	—	Excellent	At 0.5GB VRAM, runs alongside any model with negligible impact.
Stable Diffusion XL 1.0	FP16	—	Good	~15-20 seconds per 1024x1024 image at 30 steps. SDXL requires ~6.5GB VRAM. Fits on 12GB with room for LoRA.
Whisper Large V3	FP16	—	Excellent	3.1GB VRAM at FP16. Transcribes ~10x faster than real-time. Runs on any GPU in our dataset.
Mistral 7B Instruct v0.3	Q5_K_M	33 tok/s	Good	Similar to Llama 8B performance. 6.7GB headroom.
Phi-3 Mini 3.8B Instruct	Q8_0	60 tok/s	Excellent	3.8B model runs extremely fast even on budget GPUs. 7.5GB headroom at Q8.
all-MiniLM-L6-v2	FP16	—	Excellent	At 0.25GB, runs alongside any model with zero meaningful impact.
Gemma 2 9B Instruct	Q5_K_M	30 tok/s	Good	Q5 at 6.6GB fits well on 12GB. Slightly slower than Llama 8B due to architecture differences.
Qwen 2.5 7B Instruct	Q5_K_M	33 tok/s	Good	Similar performance to Llama 8B and Mistral 7B at this size class.
DeepSeek R1 Distill Qwen 7B	Q4_K_M	38 tok/s	Good	7B distill model fits comfortably on 12GB. Good speed for reasoning tasks.
Gemma 3 12B	Q4_K_M	32 tok/s	Good	12B at Q4 fits on 12GB. Good balance for budget builds.
Gemma 3 4B	Q5_K_M	55 tok/s	Excellent	4B model runs very fast on 12GB. Minimal VRAM footprint.
Qwen 2.5 Coder 7B Instruct	Q5_K_M	36 tok/s	Good	7B coding model fits well on 12GB. Good for code completion.
InternLM 2.5 7B Chat	Q5_K_M	35 tok/s	Good	7B model fits comfortably on 12GB. Good for general tasks.
Llama 3.2 3B Instruct	Q8_0	90 tok/s	Excellent	3.21B model at Q8_0 (3.7GB) fits with 8GB headroom. Extremely fast on 360 GB/s bandwidth.
Llama 3.2 1B Instruct	Q8_0	140 tok/s	Excellent	1.24B model at Q8_0 (1.5GB). Essentially instant — even faster than 3B.
Phi-4 Mini	Q8_0	80 tok/s	Excellent	3.82B at Q8_0 (4.3GB). Slightly slower than 3B Llama due to more params. 7GB headroom.
Whisper Large V3 Turbo	FP16	—	Excellent	Processes audio in real-time. Turbo variant is ~8x faster than full Whisper Large V3. 1.6GB VRAM at FP16.
Stable Diffusion 3.5 Large	Q8_0	—	Good	Q8 variant (9GB) fits in 12GB. FP16 at 12.5GB doesn't fit. Image generation takes ~15s per image.
Gemma 3 27B	Q3_K_M	—	Not Viable	12GB VRAM insufficient. Gemma 3 27B requires at least 13.3GB at Q3_K_M. Would need 16GB+ device or CPU offloading (impractical for speed).
DeepSeek V3	Q2_K	—	Not Viable	671B MoE model requires 115GB+ even at Q2_K. 12GB is nowhere near sufficient. Would need 128GB+ unified memory or multi-GPU.

Featured in Builds

Budget AI Desktop

$753

Starter AI Desktop

$582

Buy Used

Prices and availability vary. Inspect hardware before purchasing.

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Frequently Asked Questions

What AI models can NVIDIA GeForce RTX 3060 12GB run?: The NVIDIA GeForce RTX 3060 12GB can run 22 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 3060 12GB good for AI coding?: With 12 GB, the NVIDIA GeForce RTX 3060 12GB runs 7-8B coding models at the Starter tier. Good for basic code completion.
How much VRAM does NVIDIA GeForce RTX 3060 12GB have?: The NVIDIA GeForce RTX 3060 12GB has 12 GB of GDDR6 VRAM with 360 GB/s bandwidth.
Can NVIDIA GeForce RTX 3060 12GB run 70B models?: 70B models can run on the NVIDIA GeForce RTX 3060 12GB with CPU offloading, but performance will be reduced. Consider a GPU with 48GB+ VRAM for full-speed 70B inference.
Is NVIDIA GeForce RTX 3060 12GB worth it for AI?: At $269, the NVIDIA GeForce RTX 3060 12GB offers 12 GB VRAM and runs 22 AI models. It's a good entry point for smaller models and experimentation.

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

Compatible Models

Model	Quant	Speed	Rating	Notes
Llama 3.1 8B Instruct	Q5_K_M	35 tok/s	Good	Comfortable fit with 6.2GB headroom. Good speed despite lower bandwidth.
DeepSeek Coder V2 Lite 16B	Q4_K_M	40 tok/s	Good	MoE architecture — only 2.4B active params per token. Speed closer to a 3B model despite 15.7B total. Fits at Q4 (9.1GB) with headroom.
nomic-embed-text v1.5	FP16	—	Excellent	At 0.5GB VRAM, runs alongside any model with negligible impact.
Stable Diffusion XL 1.0	FP16	—	Good	~15-20 seconds per 1024x1024 image at 30 steps. SDXL requires ~6.5GB VRAM. Fits on 12GB with room for LoRA.
Whisper Large V3	FP16	—	Excellent	3.1GB VRAM at FP16. Transcribes ~10x faster than real-time. Runs on any GPU in our dataset.
Mistral 7B Instruct v0.3	Q5_K_M	33 tok/s	Good	Similar to Llama 8B performance. 6.7GB headroom.
Phi-3 Mini 3.8B Instruct	Q8_0	60 tok/s	Excellent	3.8B model runs extremely fast even on budget GPUs. 7.5GB headroom at Q8.
all-MiniLM-L6-v2	FP16	—	Excellent	At 0.25GB, runs alongside any model with zero meaningful impact.
Gemma 2 9B Instruct	Q5_K_M	30 tok/s	Good	Q5 at 6.6GB fits well on 12GB. Slightly slower than Llama 8B due to architecture differences.
Qwen 2.5 7B Instruct	Q5_K_M	33 tok/s	Good	Similar performance to Llama 8B and Mistral 7B at this size class.
DeepSeek R1 Distill Qwen 7B	Q4_K_M	38 tok/s	Good	7B distill model fits comfortably on 12GB. Good speed for reasoning tasks.
Gemma 3 12B	Q4_K_M	32 tok/s	Good	12B at Q4 fits on 12GB. Good balance for budget builds.
Gemma 3 4B	Q5_K_M	55 tok/s	Excellent	4B model runs very fast on 12GB. Minimal VRAM footprint.
Qwen 2.5 Coder 7B Instruct	Q5_K_M	36 tok/s	Good	7B coding model fits well on 12GB. Good for code completion.
InternLM 2.5 7B Chat	Q5_K_M	35 tok/s	Good	7B model fits comfortably on 12GB. Good for general tasks.
Llama 3.2 3B Instruct	Q8_0	90 tok/s	Excellent	3.21B model at Q8_0 (3.7GB) fits with 8GB headroom. Extremely fast on 360 GB/s bandwidth.
Llama 3.2 1B Instruct	Q8_0	140 tok/s	Excellent	1.24B model at Q8_0 (1.5GB). Essentially instant — even faster than 3B.
Phi-4 Mini	Q8_0	80 tok/s	Excellent	3.82B at Q8_0 (4.3GB). Slightly slower than 3B Llama due to more params. 7GB headroom.
Whisper Large V3 Turbo	FP16	—	Excellent	Processes audio in real-time. Turbo variant is ~8x faster than full Whisper Large V3. 1.6GB VRAM at FP16.
Stable Diffusion 3.5 Large	Q8_0	—	Good	Q8 variant (9GB) fits in 12GB. FP16 at 12.5GB doesn't fit. Image generation takes ~15s per image.
Gemma 3 27B	Q3_K_M	—	Not Viable	12GB VRAM insufficient. Gemma 3 27B requires at least 13.3GB at Q3_K_M. Would need 16GB+ device or CPU offloading (impractical for speed).
DeepSeek V3	Q2_K	—	Not Viable	671B MoE model requires 115GB+ even at Q2_K. 12GB is nowhere near sufficient. Would need 128GB+ unified memory or multi-GPU.

Frequently Asked Questions

What AI models can NVIDIA GeForce RTX 3060 12GB run?

The NVIDIA GeForce RTX 3060 12GB can run 22 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 3060 12GB good for AI coding?

With 12 GB, the NVIDIA GeForce RTX 3060 12GB runs 7-8B coding models at the Starter tier. Good for basic code completion.

How much VRAM does NVIDIA GeForce RTX 3060 12GB have?

The NVIDIA GeForce RTX 3060 12GB has 12 GB of GDDR6 VRAM with 360 GB/s bandwidth.

Can NVIDIA GeForce RTX 3060 12GB run 70B models?

70B models can run on the NVIDIA GeForce RTX 3060 12GB with CPU offloading, but performance will be reduced. Consider a GPU with 48GB+ VRAM for full-speed 70B inference.

Is NVIDIA GeForce RTX 3060 12GB worth it for AI?

At $269, the NVIDIA GeForce RTX 3060 12GB offers 12 GB VRAM and runs 22 AI models. It's a good entry point for smaller models and experimentation.