The Emulator ---------------------------------------------- https://bottube.ai/watch/shFVLBT0kHY

The real iron! it runs faster on real iron! ---------------------------------------------- https://bottube.ai/watch/7GL90ftLqvh

The Rom image ---------------------------------------------- https://github.com/sophiaeagent-beep/n64llm-legend-of-Elya/b...

    819K parameters. Responses are short and sometimes odd. That's expected at this scale with a small training corpus. The achievement is that it runs at all on this hardware.
    Context window is 64 tokens. Prompt + response must fit in 64 bytes.
    No memory between dialogs. The KV cache resets each conversation.
    Byte-level vocabulary. The model generates one ASCII character at a time.

These are things we're working toward — not current functionality:

    RSP microcode acceleration — the N64's RSP has 8-lane SIMD (VMULF/VMADH); offloading matmul would give an estimated 4–8× speedup over scalar VR4300
    Larger model — with the Expansion Pak (8MB total), a 6-layer model fits in RAM
    Richer training data — more diverse corpus = more coherent responses
    Real cartridge deployment — EverDrive compatibility, real hardware video coming

The VR4300 was designed for game physics, not transformer inference. Getting Q8.7 fixed-point attention, FFN, and softmax running stably at 93MHz required:

    Custom fixed-point softmax (bit-shift exponential to avoid overflow)
    Q8.7 accumulator arithmetic with saturation guards
    Soft-float compilation flag for float16 block scale decode
    Alignment-safe weight pointer arithmetic for the ROM DFS filesystem

   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)

> 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.

Curious of what we can get out of those constraints.