If you’re looking to run Ollama and LLMs (Large Language Models) locally without spending a fortune, you’ll need a GPU with good VRAM, CUDA (for NVIDIA), or ROCm (for AMD). Choosing the right GPU can make a big difference in performance and model compatibility.
I personally use an MSI RTX 2080 SUPER, and it runs Deepseek-R1 smoothly. But if you’re looking for budget-friendly alternatives, I’ve compiled a list of solid options that balance performance, affordability, and availability.
Why a Good GPU Matters for Local AI?
LLMs require high memory bandwidth and computational power to run efficiently. The two main factors to consider when choosing a GPU for AI workloads are:
- VRAM (Video Memory): The more VRAM, the larger the models you can run. At least 8GB is recommended, but 12GB or more is ideal for smooth performance.
- CUDA vs. ROCm: NVIDIA GPUs use CUDA and TensorRT, which offer better AI optimization and software support. AMD GPUs rely on ROCm, which has improved AI support on Linux but is still less mature than NVIDIA’s ecosystem.
Best Budget NVIDIA GPUs (CUDA-Based)
NVIDIA cards are the preferred choice for AI workloads due to CUDA and TensorRT support. They tend to have better software compatibility for local AI models like LLaMA, Mistral, Deepseek, and more.
RTX 3060 (12GB VRAM) - Best Budget Pick
- Best budget option with 12GB VRAM, allowing you to run larger models smoothly.
- Good efficiency and power usage, making it ideal for AI without huge power draw.
Typically priced at $250-$350 (used or new).
**Amazon Links: (**updated 8/5/2025)
- ASUS RTX 3060 ($329.99)
- Gigabyte RTX 3060 ($349.99)
- MSI RTX 3060 ($299)
RTX 2060 Super (8GB VRAM) - Solid Budget Option
Pros
- Decent CUDA performance for smaller LLMs.
- Can be found for $180-$250 (used).
Cons
- Less VRAM than the 3060, so it struggles with larger models.
RTX 3050 (8GB VRAM) - Entry-Level Choice
Pros
- Low power consumption, great for small AI projects.
Cons
-
Slower than the RTX 3060 but can still handle lightweight models.
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Costs $170-$329 new.
Amazon Links:
- ASUS Dual GeForce RTX 3050 8Gb ($329)
Best Budget AMD GPUs (ROCm-Based)
AMD’s ROCm ecosystem is improving, but it’s still not as polished as NVIDIA’s CUDA. If you’re using Linux, these GPUs are solid choices for budget AI setups.
RX 6700 XT (12GB VRAM) - Best AMD Budget Pick
- Best AMD card for LLMs due to its 12GB VRAM.
- Better performance than RTX 3060 in raw compute power.
Costs $250-$300 (used).
RX 6750 XT (12GB VRAM) - Slightly Faster Than 6700 XT
Pros
- Improved memory bandwidth over the RX 6700 XT.
- Solid AI performance for ROCm-supported models.
Cons
- Requires Linux for best AI compatibility.
RX 6600 XT (8GB VRAM) - Budget AMD Pick
- Decent AI performance but limited VRAM for large models.
Costs $180-$220.
Amazon Link**:**
- AMD RX 6600 XT ($219)
Best Overall Picks for Budget AI Setups
- For NVIDIA: RTX 3060 (12GB) is the best option, as it balances price, VRAM, and software support.
- For AMD: RX 6700 XT (12GB) is the best choice if you’re using Linux and can configure ROCm.
? If you need an AI-capable machine on a budget, these GPUs will give you solid performance for local LLMs without breaking the bank.
Full Systems
Apple 2024 Mac Mini Desktop
I’ve currently started messing around with the Mac mini as an AI server and It actually runs better than my Main computer which runs a Geforce GTX 2080 Super. My main pc with the GTX 2080 Super gets about 30 tokens per second, I tested the Mac Mini and it gets around 40. I currently use strictly as an AI server, I’m going to write an article about this in the future.
Key Features (Low End Model)
CPU
- 10-core CPU with 4 performance cores and 6 efficiency cores
- 10-core GPU
- Hardware-accelerated ray tracing
- 16-core Neural Engine
- 120GB/s memory bandwidth
Memory
16 GB
Price: $560 - $599
Link: Amazon ($547)
Jetson Orin Nano Super
If your looking into the Nvidia Jetson Orin Nano , Stop. I originally had it listed here, but after testing the thing and doing some research, its not great for LLM. Its more of a super computer for robotics.
Final Thoughts
If you’re looking for budget-friendly GPUs for Ollama and local AI, your choice depends on your operating system and model needs:
- For best AI compatibility (Windows & Linux): RTX 3060 (12GB) is the best option.
- For best AMD budget performance (Linux only): RX 6700 XT (12GB) works great if you can configure ROCm.
? Looking for more AI hardware recommendations? Drop a comment below! ?