repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 2d ago
engeldlgado/toshllm
Run large language models locally on Intel Macs with AMD GPUs - native macOS app with Metal acceleration
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 49%Ask HN: MacBook vs. Dedicated GPU for LLM →
- PossiblePossibly related (embedding) · 47%My reasons to run local models →
- PossiblePossibly related (embedding) · 46%[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 →
- PossiblePossibly related (embedding) · 49%Gemma 4 12B - MLX Kernel →
- PossiblePossibly related (embedding) · 49%Madlad builds homebrew GPU using 8,192 RISC-V chips →
- PossiblePossibly related (embedding) · 49%Retro68: a GCC-based cross-compilation environment for 68K and PowerPC Macs - Adafruit →
- PossiblePossibly related (embedding) · 48%NASA Puts Google’s Gemma Large Language Model in Orbit →
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Related across the graph
newsNASA Puts Google’s Gemma Large Language Model in OrbitnewsMadlad builds homebrew GPU using 8,192 RISC-V chipsnewsMy reasons to run local modelsnewsRetro68: a GCC-based cross-compilation environment for 68K and PowerPC Macs - Adafruitnews[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/decodenewsAsk HN: MacBook vs. Dedicated GPU for LLMnewsGemma 4 12B - MLX Kernel