Best GPUs for Running Local Coding LLMs in 2026

For developers seeking to run coding Large Language Models (LLMs) locally, the choice of GPU is critical. The NVIDIA RTX 4090 with 24GB of VRAM is recommended for running advanced models like DeepSeek Coder 33B, offering speeds sufficient for interactive code generation. A more budget-friendly option, the RTX 4060 Ti 16GB, is suitable for smaller models such as Qwen2.5 Coder 14B and DeepSeek Coder V2 Lite, providing a good balance of performance and cost for everyday coding tasks. AI

IMPACT Enables developers to run powerful coding LLMs locally, reducing reliance on cloud services and potentially lowering costs.

RANK_REASON Article provides hardware recommendations for running specific AI models locally, focusing on practical user applications rather than a new model release or research breakthrough.

Read on dev.to — LLM tag →

• CodeLlama
• Continue.dev
• DeepSeek Coder 33B
• DeepSeek Coder V2 Lite
• GitHub Copilot
• GPT-3.5
• GPT-4
• NVIDIA RTX 3060 12GB
• NVIDIA RTX 4060 Ti 16GB
• NVIDIA RTX 4090
• Ollama
• Qwen2.5 Coder 14B
• NVIDIA RTX 3090

• infra
• product

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