MiniMax মাত্রই লঞ্চ করেছে M3.1 Flash: 428B MoE এজেন্টিক মডেল $0.15/মিলিয়ন ইনপুটে

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MiniMax has just released MiniMax M3.1 Flash on its API, priced at $0.15 per 1M input tokens. MiniMax also confirmed that Space Bunny was an earlier M3.1 Flash build. That stealth model processed over 200T tokens. For developers, the message is near-frontier agentic scores at Flash-tier cost. Model weights are due in late October, 2026. TL;DR Size: 428B total parameters, about 23B active (MoE); 1,000,000-token context Runs on: MiniMax API, M Plan and MiniMax Code today. Self-hosting hardware not disclosed; weights arrive Oct 23 Performance: Near-frontier on agentic office work, mid-pack on hard coding, all MiniMax-reported Best: Automation-Bench v1.0.6 at 62.2, the top score in MiniMax’s table Worst: Terminal Bench 4.0 at 38.1, versus 51.8 for Opus 5 What is MiniMax M3.1 Flash? MiniMax M3.1 Flash is a multimodal mixture-of-experts model from MiniMax. It targets coding, agentic office work and visual reasoning. MiniMax’s product page lists 428B total parameters and about 23B active. It also mentions sparse attention and a native visual encoder. The model accepts text, image and video input and returns text. The context window is 1,000,000 tokens. Those parameter totals match MiniMax M3, which ships at ~428B total and ~23B active. MiniMax has not published a technical report on what changed in the Flash variant. How does reasoning work in M3.1 Flash? Reasoning is always on and cannot be disabled. Developers choose from 5 effort levels: Low, Medium, High, Xhigh and Max. MiniMax recommends Max as the default. Migration matters here. Requests sending thinking.type=disabled or effort=none return an error. Reasoning arrives in a separate reasoning_content field, which may be absent. Integrations that parse inline tags from M3 need updating. How does M3.1 Flash perform on benchmarks? All scores below are MiniMax-reported. No independent replication exists yet. On the CoWork set, M3.1 Flash leads Automation-Bench v1.0.6 at 62.2. Opus 5 scores 50.3 and GPT-5.6