witcheer/local-agentic-coding-bench-8gb-vram-2026-05
agentic coding benchmark: local LLMs on 8GB VRAM can local LLMs do agentic coding (multi-turn tool calling, file creation, debugging) on consumer hardware? this dataset captures real test results. hardware GPU: NVIDIA RTX 4060 Ti 8GB CPU: Intel i7-14700F RAM: 32 GB DDR5 OS: Windows 11 + WSL2 (Ubuntu) inference: llama-server (turboquant fork of llama.cpp) what was tested two agent frameworks: Hermes Agent (NousResearch): structured tool calling… See the full description on the dataset page: https://huggingface.co/datasets/witcheer/local-agentic-coding-bench-8gb-vram-2026-05.
append 2 Gemma 4-E4B agentic rows (33 total)
add Gemma 4-E4B agentic benchmark (2 rows: portscout PASS, logpulse PARTIAL)
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initial commit