Turbo-fieldfare: Open-source engine running Gemma 4 26B in 2 GB RAM on Apple Silicon
Mirrored from r/LocalLLaMA for archival readability. Support the source by reading on the original site.
| Its a custom Swift/Metal inference engine that runs Gemma 4 26B-A4B-IT on M-series Macs with very low RAM. It uses ~2GB instead of ~14 GB. The result is reportedly 5–6 tok/s on an 8 GB M2 MacBook Air and 31–35 tok/s on an M5 MacBook Pro. It also includes an OpenAI-compatible local server with streaming and tool-call support. [link] [comments] |
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