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User asks whether purchasing an RTX 5090 and high-end PC for ~$5500 is worth it for LLM experimentation and learning, compared to cloud compute alternatives.
A benchmark shows that using vLLM with DFlash speculative decoding boosts Gemma 4 26B inference to ~578 tokens per second on a single RTX 5090, achieving a 2.56x speedup over baseline.
User reports surprisingly usable coding performance from Qwen3-27B-UD-Q6_K_XL.gguf running locally on RTX 5090 at ~50 tok/s with 200K context, marking a significant leap in local model quality.
User reports a satisfying experience running Claude Code locally via LM Studio on an RTX 5090, achieving 64k context length and 200+ tokens per second.