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Akwin123 fine-tuned Gemma-4-31B-it specifically for copywriting and creative writing tasks, achieving a +290 Elo improvement over the base model on a custom benchmark using QLoRA. The model is open-source and available on Hugging Face.
A developer is rebuilding Gemma 4 31b into a smaller 26b model by removing weak SWA layers, adding attention-based residual networks (from Moonshot), and using topK logit targets for retraining, aiming for better long context and performance.
Introduces Agentic Swarm, an open-source desktop application that orchestrates 5 AI agents using Google's Gemma-4 model, running entirely offline.
Xenova used Fable 5 to write optimized kernels achieving 255 tokens per second for Gemma 4 on WebGPU with M4, demonstrating agentic kernel optimization for on-device inference.
Google recaps its major AI updates from June 2026, including the launch of Gemini 3.5 Live Translate, Android 17, the new Google Home Speaker, and local AI models like Gemma 4 12B, alongside computer use capabilities in Gemini 3.5 Flash.
Ollama announces that Gemma 4 is now nearly 90% faster on Apple Silicon using MLX, thanks to improved multi-token prediction enabled by default, with automatic tuning to avoid slowdown.
The author gave a talk at Google on AI Agent Harness Engineering, demonstrating a Financial Agent using Gemma 4 local LLMs that ran under 15 GB RAM and performed on par with frontier models.
Meet Gemma 4 12B Agentic Fable5, a locally-run GGUF model designed for coding, terminal tasks, and agentic workflows, with 206k downloads.
Cerebras and Google DeepMind are hosting a 24-hour hackathon on June 28-29, featuring Gemma 4 models with ultra-fast Cerebras inference, with $5000 in prizes.
A multi-agent system with over 100 agents collaborates for a week to accelerate Gemma 4 on vLLM by 5x, demonstrating emergent self-organized communication and resource pooling.
An experiment with over 100 AI agents collaborating for a week to improve Gemma 4 inference speed in vLLM achieved a 5x speedup, revealing emergent behaviors like self-policing, division of labor, and communal knowledge sharing.
Tweet announces Gemma 4 31B multimodal model with high speed, calling it a step towards superintelligence.
A developer demonstrates running Gemma 4 26B MoE model locally on an 8GB RTX 4060 with Hermes agent to fully automate backtesting of trading strategies, highlighting the growing capability of local LLMs as autonomous agents.
A user asks why Gemma 4 26b receives less attention compared to Qwen models, sharing their experience using these models for a personal assistant project on a 3090.
An analysis exploring why Gemma 4, despite advantages like QAT and vision support, lacks community finetunes compared to Mistral, and whether community inertia will eventually shift.
Qt Creator 20 now supports local AI coding assistants via the Agent Client Protocol, enabling integration with open-weight models like GPT-OSS and Gemma 4 running on consumer hardware.
The Gemma 4 QAT 31B model demonstrates improved behavior with KV cache quantization, suggesting enhanced inference efficiency.
Discusses running a Q6 quantized version of the Gemma 4 31B model on a dual 9060 XT GPU configuration, likely for local inference.
A new fine-tuned version of Gemma 4 12B, trained on Fable 5's reasoning, achieves a significant jump in agentic coding benchmarks (from 15% to 55%) and can run locally on an 8GB VRAM GPU using a custom fork of llama.cpp.
User reports that Gemma 4 26b outperforms Qwen 3.5/3.6 for language learning and scientific queries, despite being behind in coding tasks, and invites discussion on other non-coding use cases for small MoE models.