A user shares their journey into local large language model (LLM) usage, starting with skepticism in early 2025 and evolving to a dedicated enthusiast. They detail their hardware upgrades, including a dual ASUS PRIME RTX 5060 Ti setup, and their experiences with various models like Mistral Nemo, Magistral Small, Gemma 3 and 4, and Qwen3.8. The user highlights the significant advancements in llama.cpp, particularly with the introduction of tensor split and MTP features, which dramatically improved generation speeds and enabled them to rely entirely on local LLMs for most tasks. AI
IMPACT Demonstrates the rapid progress and increasing capability of local LLM deployments, potentially reducing reliance on cloud-based solutions for many users.
RANK_REASON User's personal experience and reflection on the progress of local LLMs and the llama.cpp project.
- AMD Radeon RX 7800 XT 16GB
- DeepSeek v3.2
- Gemma 3
- Gemma 4
- koboldcpp
- llama.cpp
- lmstudio
- Magistral Small 2507 Vision Rebased frankenmerge
- Mistral Nemo
- Mistral Small 3.2
- RTX 5060 Ti 16GB
- ollama
- Qwen3.8
- SillyTavern
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