witcheer/windows-rtx-4060ti-8gb-moe-offload-bench-2026-05
RTX 4060 Ti 8GB — Multi-Model Benchmark (2026-05) practitioner benchmarks on consumer hardware (8GB VRAM, 32GB RAM). 10 models tested, covering MoE expert offload, hybrid SSM architectures, dense models, MLA, dense partial GPU offload, and the 1B speed ceiling. all runs on the same physical rig, same methodology. current leaderboard (decode tok/s at sweet spot) model active params GGUF size sweet spot tok/s quality (6 tests) architecture Llama 3.2 1B… See the full description on the dataset page: https://huggingface.co/datasets/witcheer/windows-rtx-4060ti-8gb-moe-offload-bench-2026-05.
append 5 Gemma 4-E4B rows to combined JSONL (62 total rows)
add Gemma 4-E4B benchmark data (5 rows, 2026-05-21)
add gpt-oss-20b source file to source/
fix: remove stray root JSONL that broke dataset viewer
fix: merge gpt-oss-20b rows into main file, remove stray root JSONL
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fix data files table: source/ not data/
remove file from data/ (conflicts with dataset viewer, moved to source/)
move Qwen3.6 27B source file to source/ directory
merge Qwen3.6 27B dense rows into main dataset (47 -> 52 rows)
update README: add Qwen3.6 27B dense (9th model, campaign complete)
add Qwen3.6 27B dense benchmark (MoE vs dense control experiment)
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Upload README.md with huggingface_hub
Upload folder using huggingface_hub
Upload folder using huggingface_hub
Upload folder using huggingface_hub
Upload folder using huggingface_hub
add LFM2 24B A2B data file (6 rows, ncmoe sweep + context scaling)
fix: restore merged file with all models (Qwen + Gemma + LFM2, 19 rows)
add LFM2 24B A2B — ncmoe sweep + stress test (6 rows)
add gemma 4 26B A4B ncmoe sweep (6 data points)
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Upload data/bench-2026-05-07.jsonl with huggingface_hub
Create data/bench-2026-05-06.jsonl
Create README.md
initial commit
