ๆณจๅ†Œๅนถๅˆ†ไบซ้‚€่ฏท้“พๆŽฅ๏ผŒๅฏ่Žทๅพ—่ง†้ข‘ๆ’ญๆ”พไธŽ้‚€่ฏทๅฅ–ๅŠฑใ€‚

David Hendrickson
@TeksEdge
CEO & Founder | PhD | Startup Advisor | @Columbia | Author Generative Software Engineering | ๐Ÿ”” Follow for AI & Vibe Coding Tips ๐Ÿ‘‡
ๅŠ ๅ…ฅ July 2023
549 ๆญฃๅœจๅ…ณๆณจ    11.2K ็ฒ‰ไธ
๐Ÿ“ฐ A 1.56GB local model just took the #1# spot for open models under 4B on Artificial Analysis. Let's run it on ThumbLLM. OpenBMB released MiniCPM5-2B TODAY. Stats ๐Ÿ‘‡ ๐Ÿง  2.52B dense parameters ๐Ÿ’พ Q4_K_M GGUF: just 1.56GB ๐Ÿ“š 131K native context โš–๏ธ Apache 2.0 ๐Ÿฆ™ llama.cpp ๐ŸŸข Ollama ๐Ÿ–ฅ๏ธ LM Studio ๐ŸŽ MLX ๐Ÿค– Native tool calling + agent training Artificial Analysis Intelligence Index v4.2 ... ๐Ÿฅ‡ MiniCPM5-2B โ†’ 15 Qwen3.5-4B Reasoning โ†’ 14* Qwen3.5-9B Reasoning โ†’ 15* Granite 4.2 3B โ†’ 11 *Qwen scores are estimated by Artificial Analysis. So a 1.56GB Q4 GGUF is landing in the same AA Intelligence Index tier as Qwen3.5-9B. ๐Ÿค– GDPval-AA v2 Elo โ†’ 831 ๐Ÿฆ ฯ„ยณ-Banking โ†’ 21% โšก 19K output tokens/task vs 56K for Ling 3.0 Tiny OpenBMB even released the training data and an official DSpark speculative decoding model. No trustworthy local tok/s numbers yet. That is the benchmark I want next. ๐Ÿ”ฅ Let's run it on ThumbLLM! ๐Ÿ”— HF /openbmb/MiniCPM5-2B
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