# b11569: metal : fix mul_mat_id with duplicate ids (#30373)

> **Key Architectural Takeaway:** metal : fix mul_mat_id limits and kernel name metal : fix mul_mat_id with duplicate ids kernel_mul_mm_id_map0 assumed at most one match per token and a fixed capacity of ne21 entries per expert, which produced wrong or dropped output rows and could overflow into the slice of the next expert when the ids contain duplicates.

**Published:** 2026-10-12T10:31:41+00:00  
**Source:** Llama.cpp Tensor Acceleration  
**Category:** ai-local-edge  
**Canonical URL:** https://fosswire.org/news/b11569-metal-fix-mulmatid-with-duplicate-ids-30373.html  

## Executive Summary
metal : fix mul_mat_id limits and kernel name metal : fix mul_mat_id with duplicate ids kernel_mul_mm_id_map0 assumed at most one match per token and a fixed capacity of ne21 entries per expert, which produced wrong or dropped output rows and could overflow into the slice of the next expert when the ids contain duplicates. build a compact per-expert list of the (token, slot) entries instead: pass 1 counts the entries of every expert, thread 0 computes the offsets of the expert slices (tpe now holds [base, count]) pass 2 writes the entries with one unconditional store per token (conditional stores of divergent lanes are very slow), the dummy value of the tokens without a...

## Architectural & Systems Analysis
From an artificial intelligence architecture, model weights governance, and inference efficiency perspective:

- **Weights Accessibility & Sovereignty:** Evaluates whether weights are open for private self-hosting or locked behind centralized cloud APIs.
- **Quantization & Edge Performance:** Kernel optimizations (4-bit/8-bit GGUF, AWQ, EXL2) allow high tokens-per-second on consumer GPUs and Apple Silicon.
- **Reasoning & Architectural Scaling:** Scrutinizes mixture-of-experts (MoE), attention mechanisms, and fine-tuning datasets against open community benchmarks.

## Impact on the Open Ecosystem
Protects developers and enterprises from proprietary black-box entrapment, fostering auditable, sovereign AI infrastructure.