The sgai_rsp_matmul_q4() stub is planned for RSP microcode:
DMA Q4 weight tiles into DMEM (4KB at a time)
VMULF/VMADH vector multiply-accumulate for 8-lane dot products
Estimated 4-8× speedup over scalar VR4300 inference
rsp is the gift that keeps on giving; such a forwards-looking architecture (shame about the rambus latency tho)
> World's First LLM-powered Nintendo 64 Game — nano-GPT running on-cart on a 93MHz VR4300
> This isn't just a tech demo — it's a tool for N64 homebrew developers. Running an LLM natively on N64 hardware enables game mechanics that were impossible in the cartridge era:
> AI analyzes play style and adjusts on the fly
> NPCs that remember previous conversations and reference past events
> In-game level editors where you describe what you want to build
...anyone who has ever used very small language models before should see the problem here. They're fun and interesting, but not exactly, um, coherent.
The N64 has a whopping 8 megabytes (!) of memory, and that's with the expansion pack!
I'm kind of confused, especially since there are no demonstration videos. Is this, um, real? The repository definitely contains source code for something.
https://github.com/sophiaeagent-beep/n64llm-legend-of-Elya/b...
It feels very much like it’s cobbled together from the libdragon examples directory. Or, they use hardware acceleration for the 2D sprites, but then write fixed-width text to the frambuffer with software rendering.
Curious of what we can get out of those constraints.