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DeepSeek V4 Flash benchmarks faster than Anthropic's Sonnet and Opus on coding tasks

A follow-up benchmark indicates that the DeepSeek V4 Flash model, when run locally on dual RTX Pro 6000 GPUs, can complete coding tasks significantly faster than Anthropic's Sonnet and Opus models. While DeepSeek V4 Flash achieves quality comparable to Sonnet, it performs the tasks approximately three times quicker than Sonnet. The benchmark also included Qwen 3.6 models as reference points, highlighting the increasing viability of local models for complex tasks, though Opus and Fable models still lead in overall quality. AI

IMPACT Local models like DeepSeek V4 Flash are becoming competitive with API-based models in speed for coding tasks, potentially reducing reliance on cloud services for certain applications.

RANK_REASON The cluster reports on a benchmark comparing the performance of different LLMs on coding tasks, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

DeepSeek V4 Flash benchmarks faster than Anthropic's Sonnet and Opus on coding tasks

COVERAGE [1]

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

    Follow-up: DeepSeek V4 Flash on 2x RTX PRO 6000 finishes real coding tasks faster than Sonnet and Opus, at about Sonnet quality

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1um84bd/followup_deepseek_v4_flash_on_2x_rtx_pro_6000/"> <img alt="Follow-up: DeepSeek V4 Flash on 2x RTX PRO 6000 finishes real coding tasks faster than Sonnet and Opus, at about Sonnet quality" src="https://…