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MiniMax M3.1 Flash bug fixes cost 7x more at default effort, study finds

By PulseAugur Editorial · [2 sources] ·

A new benchmark study has evaluated the performance and cost of MiniMax M3.1 Flash, a frontier multimodal coding model, across its five "effort" levels. The study found that the model consistently produced correct bug fixes regardless of the effort setting, with "low" effort being the most cost-effective. When the effort level was omitted, the model defaulted to its highest and most expensive setting, yielding no measurable improvement in quality for the tested task. The research also noted that the model's "thinking" feature, which is always on, contributes to token usage and cost, particularly for longer prompts. AI

IMPACT The study highlights the significant cost implications of default settings in AI models, suggesting users should explicitly manage effort levels for optimal efficiency.

RANK_REASON The cluster details a benchmark study measuring the performance and cost of an AI model across different settings.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

MiniMax M3.1 Flash bug fixes cost 7x more at default effort, study finds

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The cluster details a benchmark study measuring the performance and cost of an AI model across different settings.
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2 independent sources
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model release, product
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COVERAGE [2]

  1. dev.to — LLM tag TIER_1 English(EN) · AIHubMix ·

    Measuring MiniMax M3.1 Flash's Five Effort Levels on One Bug Fix

    <p><strong>TL;DR:</strong> We ran the same two-bug fix through MiniMax M3.1 Flash at all five effort levels plus "omitted", three runs each, and graded every answer against 215 hidden tests. Every run passed. The omitted default, which MiniMax documents as <code>max</code>, avera…

  2. dev.to — LLM tag TIER_1 English(EN) · AIHubMix ·

    MiniMax M3.1 Flash (ex-Space Bunny) on the API: Specs, Price, and a Measured Bug-Fix Cost

    <p><strong>Result first:</strong> MiniMax M3.1 Flash is now callable per token on AIHubMix as <code>minimax-m3.1-flash</code> ($0.165 input / $0.66 output per million tokens). On a two-bug fix in one Python function, it passed all 215 hidden tests at both settings we compared. Le…

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