Best GPUs Under $1,000 for Local LLMs: RTX 3090 vs. RTX 5080

For users looking to run large language models locally on a budget of under $1,000, a used RTX 3090 is recommended due to its 24GB of VRAM, which is essential for handling models like CodeLlama 34B and Qwen 2.5 32B. Alternatively, for those prioritizing new hardware with a warranty and lower power consumption, the RTX 5070 Ti offers excellent value, capable of running 7B to 13B models efficiently. The RTX 5080 is presented as the top-tier new option for maximum inference speed within the 7B-13B model range. AI

IMPACT Guides users on selecting cost-effective hardware for running large language models locally, impacting the accessibility of AI experimentation.

RANK_REASON Article provides a ranked comparison of hardware for a specific use case (local LLMs) within a price constraint, rather than a new release or major industry event.

Read on dev.to — LLM tag →

• CodeLlama 34B
• DeepSeek-R1 32B
• GeForce RTX 4070 Ti Super
• Llama 2 13B
• Llama-3.1:8b
• RTX 5070 Ti
• Qwen 2.5 32B
• RTX 3090
• RTX 3090 Ti
• RTX 4090
• RTX 5070
• RTX 5080

• infra

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