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DeepSeek v4 Pro's large size questioned against performance

The user questions the value of DeepSeek v4 Pro, a large open-source model with 1.6 trillion parameters, suggesting its performance is not commensurate with its size. They compare it unfavorably to smaller models like GLM 5.1 and Kimi K2.6, which are considered superior despite having fewer parameters. The user also notes that MiniMax M3 and MiMo v2.5 Pro offer better performance at similar or smaller scales. They ponder if the model is overhyped, if its preview status is a factor, or if inference hardware, like Huawei's, is more critical than raw model scores. AI

IMPACT Raises questions about the efficiency of large parameter counts versus actual performance and the role of inference hardware.

RANK_REASON User opinion piece questioning the performance of a specific model release.

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  1. r/LocalLLaMA TIER_1 English(EN) · /u/ihatebeinganonymous ·

    DeepSeek v4 Pro is too big for such a "midrange" performance, or am I missing something?

    <!-- SC_OFF --><div class="md"><p>Hi. </p> <p>DeepSeek v4 Pro has 1.6T parameters, probably the largest in open models, or at least one of the largest.</p> <p>Yet it's not the best/most performance open model, considering a wide variety of definitions of &quot;best&quot;. Indeed,…