What AI models can NVIDIA GeForce RTX 5060 8GB run?

The NVIDIA GeForce RTX 5060 8GB can run 52 AI models. Top performers include all-MiniLM-L6-v2, nomic-embed-text v1.5, Llama 3.2 1B Instruct. See the full compatibility table above for speeds and quality ratings.

Is NVIDIA GeForce RTX 5060 8GB good for AI coding?

With 8 GB, the NVIDIA GeForce RTX 5060 8GB has limited VRAM for AI coding workflows.

How much VRAM does NVIDIA GeForce RTX 5060 8GB have?

The NVIDIA GeForce RTX 5060 8GB has 8 GB of GDDR7 VRAM with 448 GB/s bandwidth.

Can NVIDIA GeForce RTX 5060 8GB run 70B models?

70B models can run on the NVIDIA GeForce RTX 5060 8GB with CPU offloading, but performance will be reduced. Consider a GPU with 48GB+ VRAM for full-speed 70B inference.

Is NVIDIA GeForce RTX 5060 8GB worth it for AI?

At $299, the NVIDIA GeForce RTX 5060 8GB offers 8 GB VRAM and runs 52 AI models. It works for smaller models and experimentation.

Build My Rig

Desktop GPU

NVIDIA GeForce RTX 5060 8GB

8 GB GDDR7 · 448 GB/s

From

$299

Estimated street price

VRAM

8 GB

Bandwidth

448 GB/s

TDP

145W

Models

Tier

Limited

The NVIDIA GeForce RTX 5060 8GB with 8 GB GDDR7 VRAM can handle 52 AI models across embedding, ai_building, coding. Best performance: all-MiniLM-L6-v2 at 9775 tok/s (excellent). Current price: approximately $299.

Source: OwnRig methodology

VRAM

8 GB

Bandwidth

448 GB/s

Memory Type

GDDR7

TDP

145W

Form Factor

2-slot, 241mm

Builder Capability: Limited

Insufficient VRAM for most AI coding workflows.

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

52 models


all-MiniLM-L6-v2	FP16	9775 tok/s	Excellent
Arcee Trinity Nano 6B	Q8_0	55 tok/s	Excellent
Code Llama 34B Instruct	Q2_K	–	Not viable
Codestral 22B	Q3_K_M	–	Not viable
Command R 35B	Q2_K	–	Not viable
DeepSeek Coder V2 Lite 16B	Q3_K_M	52 tok/s	Good
DeepSeek R1 Distill Qwen 32B	Q2_K	–	Not viable
DeepSeek R1 Distill Qwen 7B	Q4_K_M	37 tok/s	Good
DeepSeek V3	Q2_K	–	Not viable
FLUX.1 Dev	Q4_K_M	–	Marginal
Gemma 2 27B Instruct	Q3_K_M	–	Not viable
Gemma 2 9B Instruct	Q4_K_M	32 tok/s	Good
Gemma 3 12B	Q3_K_M	21 tok/s	Marginal
Gemma 3 27B	Q3_K_M	–	Not viable
Gemma 3 4B	Q5_K_M	63 tok/s	Excellent
Gemma 4 E2B	Q8_0	47 tok/s	Good
Gemma 4 E4B	Q6_K	37 tok/s	Good
GigaChat Lightning 10B	Q4_K_M	74 tok/s	Acceptable
InternLM 2.5 7B Chat	Q4_K_M	35 tok/s	Good
Llama 3.1 70B Instruct	Q2_K	–	Not viable
Llama 3.1 8B Instruct	Q4_K_M	37 tok/s	Good
Llama 3.2 1B Instruct	Q8_0	109 tok/s	Excellent
Llama 3.2 3B Instruct	Q8_0	75 tok/s	Excellent
Llama 3.3 70B Instruct	Q2_K	–	Not viable
LLaVA 1.6 13B	Q3_K_M	25 tok/s	Marginal
Mistral 7B Instruct v0.3	Q4_K_M	36 tok/s	Good
Mistral Small 24B Instruct	Q3_K_M	–	Not viable
Mixtral 8x7B Instruct	Q4_K_M	–	Not viable
nomic-embed-text v1.5	Q8_0	4830 tok/s	Excellent
NVIDIA Nemotron-3-super-120B-A12B	Q2_K	–	Not viable
Phi-3 Medium 14B Instruct	Q3_K_M	23 tok/s	Marginal
Phi-3 Mini 3.8B Instruct	Q5_K_M	60 tok/s	Excellent
Phi-4 14B	Q3_K_M	22 tok/s	Marginal
Phi-4 Mini	Q5_K_M	63 tok/s	Excellent
Qwen 2.5 14B Instruct	Q3_K_M	20 tok/s	Marginal
Qwen 2.5 72B Instruct	Q2_K	–	Not viable
Qwen 2.5 7B Instruct	Q4_K_M	35 tok/s	Good
Qwen 2.5 Coder 32B Instruct	Q2_K	–	Not viable
Qwen 2.5 Coder 7B Instruct	Q4_K_M	36 tok/s	Good
Qwen3-14B Instruct	Q3_K_M	21 tok/s	Acceptable
Qwen3-8B Instruct	Q5_K_M	28 tok/s	Acceptable
Qwen3.5-27B	Q3_K_M	–	Not viable
Qwen3.5-397B (MoE)	Q2_K	–	Not viable
Qwen3.6-27B	Q3_K_M	–	Not viable
QwQ 32B Preview	Q2_K	–	Not viable
Stable Diffusion 3 Medium	FP16	–	Good
Stable Diffusion 3.5 Large	Q8_0	–	Not viable
Stable Diffusion XL 1.0	FP16	–	Good
StarCoder 2 15B	Q3_K_M	18 tok/s	Marginal
Whisper Large V3	Q5_K_M	–	Excellent
Whisper Large V3 Turbo	FP16	–	Excellent
Yi 1.5 34B Chat	Q2_K	–	Not viable

Showing 52 of 52 entries

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FAQ

Frequently Asked Questions

What AI models can NVIDIA GeForce RTX 5060 8GB run?: The NVIDIA GeForce RTX 5060 8GB can run 52 AI models. Top performers include all-MiniLM-L6-v2, nomic-embed-text v1.5, Llama 3.2 1B Instruct. See the full compatibility table above for speeds and quality ratings.
Is NVIDIA GeForce RTX 5060 8GB good for AI coding?: With 8 GB, the NVIDIA GeForce RTX 5060 8GB has limited VRAM for AI coding workflows.
How much VRAM does NVIDIA GeForce RTX 5060 8GB have?: The NVIDIA GeForce RTX 5060 8GB has 8 GB of GDDR7 VRAM with 448 GB/s bandwidth.
Can NVIDIA GeForce RTX 5060 8GB run 70B models?: 70B models can run on the NVIDIA GeForce RTX 5060 8GB with CPU offloading, but performance will be reduced. Consider a GPU with 48GB+ VRAM for full-speed 70B inference.
Is NVIDIA GeForce RTX 5060 8GB worth it for AI?: At $299, the NVIDIA GeForce RTX 5060 8GB offers 8 GB VRAM and runs 52 AI models. It works for smaller models and experimentation.

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See every AI model it supports, expected performance, and how to build around it.

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