fahd-mirza

Overview

Fahd Mirza is a prominent ai-educator and content-creator specializing in local AI deployment, inference optimization, and model fine-tuning. His content bridges the gap between frontier research and practical local implementation, focusing heavily on llamacpp, unsloth, and speculative decoding techniques.

Recent Work & Topics

• Local Deployment & Inference:
  • Tutorials on deploying MiniMax-M2.7 via llama.cpp quantization.
  • Advanced stacked speculative decoding (MTP + Ngram) in Llama.cpp for Qwen3.6.
  • EdgeQuake framework: a high-performance local Rust Graph-RAG system using ollama.
  • Introduction to llama.cpp’s new Router Mode for native hot-swappable local LLM switching.
  • Review of MiniCPM-1B for efficient on-device hybrid reasoning.
  • Introduction to Bonsai Image for local 1-bit image generation.
  • DwarfStar for native DeepSeek V4 Flash local inference.
  • Local deployment of NVIDIA Cosmos 3, an omnimodal world model for Physical AI and robotics.
• Fine-Tuning & Optimization:
  • Fine-tuning Gemma-4 E2B with custom datasets using unsloth.
  • Inference acceleration guides via TurboQuant and DFlash speculative inference.
  • New advancements in Luce DFlash, including Adaptive PFlash for self-tuning prefill compression on long contexts using a Hermes Agent.
• Model Reviews & Analysis:
  • Review of SmolLM3 and MiniMax M3 (frontier coding, native multimodality, sparse attention).
  • Analysis of NVIDIA Nemotron 3 Ultra (550B parameter model).
• Latest Updates (June 2026):
  • Key AI Developments: Claude Fable 5 Export Controls, DiffusionGemma, Coding Agents

References

• Key AI Developments: Claude Fable 5 Export Controls, DiffusionGemma, Coding Agents

Source Notes

• 2026-06-14: Key AI Developments: Claude Fable 5 Export Controls, DiffusionGemma, Coding Agents · ▶ source
• 2026-06-10: Google QAT vs. Unsloth QAT: Gemma 4 12B Performance Comparison · ▶ source
• 2026-06-10: Gemma 4 Chat Template Fix: Preserving Reasoning for Enhanced Agentic Performance · ▶ source
• 2026-06-09: Gemma 4 Was Broken for Agents - Google Just Fixed It · ▶ source
• 2026-06-06: Miso TTS 8B Emotive Text-to-Speech Model: Installation and Performance Review · ▶ source
• 2026-06-05: NVIDIA Nemotron 3 Ultra: Open LLM Agent Optimizes Fast API Performance · ▶ source
• 2026-06-03: Adaptive PFlash and Hermes Agent: Self-Tuning LLM Prefill for Long Contexts · ▶ source
• 2026-06-02: NVIDIA Cosmos 3: Omnimodal World Model for Physical AI Robotics · ▶ source
• 2026-06-01: MiniMax M3: Open-Weight LLM’s Frontier Coding, Native Multimodality, and Sparse Attention · ▶ source
• 2026-05-30: Weekly AI Developments: Opus 4.8, Step Audio 3, Bonsai Image (May 2026) · ▶ source
• 2026-05-28: DwarfStar: Native DeepSeek V4 Flash Local Inference with Persistent KV Cache · ▶ source
• 2026-05-28: Bonsai Image: Local 1-bit Image Generation Through Extreme Quantization · ▶ source
• 2026-05-26: MiniCPM-1B: Efficient 1B-Parameter LLM for On-Device Hybrid Reasoning · ▶ source
• 2026-05-22: llama.cpp Router Mode: Native Hot-Swappable Local LLM Switching · ▶ source
• 2026-05-22: EdgeQuake: Local Rust Graph-RAG with Ollama for Improved Knowledge Retrieval · ▶ source
• 2026-05-20: MTP + Ngram Stacked Speculative Decoding in Llama.cpp for LLM Inference · ▶ source
• 2026-05-18: GPU Deployment via llama.cpp Quantization · ▶ source
• 2026-05-13: TurboQuant & DFlash: Accelerating Local LLM Inference with Enhanced Context · ▶ source
• 2026-05-11: NVIDIA Nemotron Elastic: Bundling Three LLMs for Flexible Deployment · ▶ source
• 2026-05-10: ERNIE 5.1: Baidu’s AI Model - High Performance, Cost-Efficient, Multimodal Capabilities · ▶ source
• 2026-05-09: Local Deep Research: Local AI Assistant for Comprehensive Private Information Synthesis · ▶ source
• 2026-05-06: Google Gemma 4 MTP Drafters: Accelerating Inference Speed with Speculative Decoding · ▶ source
• 2026-05-03: Luce PFlash: 10x Faster AI Model Prompt Prefill on Local GPUs · ▶ source
• 2026-04-19: Qwen 36-35B Full Precision vs Ollama Quantized Performance-Memory Trade-off · ▶ source
• 2026-04-12: MiniMax M27 Open Source LLM Technical Overview and Deployment Summary · ▶ source
• 2026-04-10: Gemma 4-E2B LLM Fine-Tuning Custom Dataset Unsloth Local Tutorial · ▶ source
• 2026-04-08: Gemma 4-E2B LLM Fine-Tuning: Custom Dataset & Unsloth Local Tutorial · ▶ source
• 2026-04-07: Gemma 4-E2B LLM Fine-Tuning: Custom Dataset & Unsloth Local Tutorial · ▶ source