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MobileMoE: Scaling On-Device Mixture of Experts
Paper • 2605.27358 • Published • 15 -
DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices
Paper • 2605.10933 • Published • 4 -
Efficient Code Embeddings from Code Generation Models
Paper • 2508.21290 • Published • 21 -
Diffusion is a code repair operator and generator
Paper • 2508.11110 • Published
🏝️ On Vacation
Aditya Tiwari
SyncreticAI
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liked a model about 8 hours ago
InternScience/Agents-A1-4B reacted to Banaxi-Tech's post with 🔥 about 11 hours ago
We're excited to release BananaMind 2 Micro, our smallest model yet.
It fits a compact architecture in only 2.9M parameters achieving the highest parameter efficiency on BananaMind Base Bench against comparable models.
It achieves comparable performance to GPT S2 5M and GPT S 5M at almost half the size while beating CMA 1M Mini.
BananaMind 2 Micro achieved the #1 spot on the Open SLM Leaderboard for the sub 3M category (not added yet but it achieves #1)
For the training we used Muon + the XSA Refresh Gate with a 5e-2 lr for Muon and 4e-3 for the 1D weights.
Its score on our efficiency measure is 0.326 getting the first place with Syn 2.6M on the second place scoring 0.291 and GPT S 5M at 0.235*
Check it out at https://huggingface.co/BananaMind/BananaMind-2-Micro and follow us at:
@vovaRL
@DedeProGames
@Banaxi-Tech
https://huggingface.co/BananaMind
Our new releases aren't stopping 🚀 August 13-14 BananaMind 2 Pro liked a model about 1 month ago
TopAI-1/Pixel-1Organizations
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MobileMoE: Scaling On-Device Mixture of Experts
Paper • 2605.27358 • Published • 15 -
DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices
Paper • 2605.10933 • Published • 4 -
Efficient Code Embeddings from Code Generation Models
Paper • 2508.21290 • Published • 21 -
Diffusion is a code repair operator and generator
Paper • 2508.11110 • Published
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