Local math LLM in action: Qwen2.5-Math-7B-Instruct.Q6_K solving calculus and quantum mechanics problems.

I tested it with problems from my university exams (curve length, extrema, gradient fields, 2D quantum box). Calculus worked surprisingly well.

I might also test it on matrix-related problems in the future.

Running fully local on AMD + ROCm.

Model quirks

- Curve length: Interprets inputs context-sensitively, e.g., e-t is correctly read as e^(-t).
- Gradient fields: Often overshoots and automatically computes the antiderivative; needed a stop condition.
- Step-by-step: Solves problems in a very textbook-like manner; some steps could be skipped when doing calculations by hand.

Video workflow:

- Recorded with OBS
- Edited in Kdenlive
- Transcoded with VAAPI (H.264)

No cloud, real hardware.
Everything runs on Linux + Text Generation Web UI (FOSS), so anyone can set this up.
No GPU? No problem, you can also run it using PyTorch’s CPU backend, just much slower.

Background music: Evanescence - Haunted (https://www.youtube.com/watch?v=tjDlL87sHMw)

#LocalAI #LLM #Qwen #MathAI #FOSS #GenerativeAI #Linux #ROCm #math