JetBrains Mellum 2: a really good and performant model
Original: Jetbrains Mellum 2: a really good and performant model
A Reddit user reports strong local speed and tool-use results from JetBrains Mellum 2 on AMD hardware.
A r/LocalLLaMA user shared informal impressions of JetBrains Mellum 2, focusing on local coding-style tasks and tool calls. On an AMD Radeon RX 7900 XT with llama.cpp Vulkan and 131K context, the model reportedly generated around 111 tokens/s and stayed above 100 tokens/s near full context. The author stresses this is not a scientific benchmark, but a practical workflow-oriented test.
這篇 r/LocalLLaMA 貼文是使用者對 JetBrains Mellum 2 的個人實測心得，主軸不是嚴格學術 benchmark，而是以日常開發任務、工具呼叫與本機推論速度來評估模型實用性。作者測試的是 JetBrains/Mellum2-12B-A2.5B-Thinking，這是一個 12B MoE 模型，每次啟用約 2.5B 參數。測試環境包含 AMD Radeon RX 7900 XT 20GB、AMD Ryzen 9 3900X、128GB DDR4 RAM，後端使用 llama.cpp Vulkan b9544，context 設為 131,072 tokens，KV cache 使用 bf16。作者回報 prompt eval 約 492.7 tokens/s，生成速度約 111.2 tokens/s，約 9ms/token，並表示即使在約 130K context 下，生成速度也沒有低於 100 tokens/s。
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