Local models went from mostly useless to actually useful really fast. What changed?
Mirrored from r/LocalLLaMA for archival readability. Support the source by reading on the original site.
| Mitchell Hashimoto had a good point earlier: local models went from basically useless to actually useful in what feels like one year. I think thats pretty accurate. A year ago I mostly treated local models like toys for privacy, simple chat, or small RAG tasks. Now people are actually using Gemma, Qwen, GLM, Kimi, etc. for coding, private docs, local workflows and even replacing some API calls. I dont think they fully replace the best closed models for long repo work yet. The gap is still obvious when the task needs planning, context, and fixing its own mistakes. But the jump in usable quality feels real. For people running local models every day, what changed the most for you? Better base models, better quants, better tools like llama.cpp/Ollama, more VRAM or something else? [link] [comments] |
More from r/LocalLLaMA
-
Palantir CEO rages against closed models
Jul 2
-
SenseNova-U1-8b-MoT-Infographic-V2 (released yesterday) - An open source SOTA beast for infographic design and image editing.
Jul 2
-
[Benchmark] Kimi K2.7 Code Q3 on Mac Studio M3 Ultra + RTX PRO 6000 over llama.cpp RPC: prefill improves, no changes in token generation/decode
Jul 2
-
They fit! Mostly.... 2x 3090, Thermaltake Core p3
Jul 2
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.