What Is MiniMax M3.1 Flash?MiniMax M3.1 Flash 是什么？
MiniMax M3.1 Flash is MiniMax's faster, cheaper successor to the June release M3, launched on October 19, 2026. It is a multimodal mixture-of-experts model with 428B total parameters and only about 23B activated per token, a 1M-token context window (up to 524,288 output tokens), and text+image+video input. Notably, MiniMax confirmed that the anonymous model "Space Bunny" — which topped two developer leaderboards in late September with 200T+ tokens processed — was an early build of M3.1 Flash.MiniMax M3.1 Flash 是 MiniMax 2026 年 10 月 19 日发布的 M3（6 月版）继任者，主打更快更便宜。它是多模态混合专家（MoE）模型：428B 总参数，每次推理仅激活约 23B；100 万上下文（输出最高 524,288 token），支持文本+图像+视频输入。值得一提的是：MiniMax 官方确认，9 月底登顶两家开发者排行榜的神秘模型 "Space Bunny"（处理量超 200T token）正是 M3.1 Flash 的早期版本。
API pricing is a flat $0.15 input / $0.60 output per million tokens, with cached input reads at $0.015 — about half of M3's standard token rates. Prices are per the official site.API 定价一刀切：$0.15 输入 / $0.60 输出每百万 token，缓存输入 $0.015，约为 M3 标准 token 费率的一半。价格以官网为准。
M3.1 Flash is MiniMax's sharpest answer to the 2026 price war: 428B-scale MoE at $0.15/$0.60 per MTok is genuine flagship-adjacent capability at budget-tier cost, and the Space Bunny reveal gives it real credibility — it didn't debut on a press release, it debuted on leaderboards. The vendor numbers (Automation-Bench 62.2, DeepSWE 73.7) look strong for agentic office work, but independent testing is more sober: 42–43 on the AA Intelligence Index and a flagged high hallucination tendency. The honest trade-off is reasoning-always-on: no thinking-free mode means every call burns reasoning tokens, so short, simple tasks may cost more than the headline rate implies. Verdict: a top value pick for long-context, high-volume agent workloads where you can control effort levels — but budget for the always-on reasoning, and verify the HF license before building on self-hosting.
M3.1 Flash 是 MiniMax 对 2026 价格战最锋利的回应：428B 级 MoE 卖 $0.15/$0.60 每百万 token，是预算级价格里的准旗舰能力；Space Bunny 揭面也给了它真凭实据——它不是靠发布会出道，是靠榜单出道。官方数据（Automation-Bench 62.2、DeepSWE 73.7）在 Agent 办公场景很漂亮，但第三方实测更冷静：AA 智能指数 42–43，且有较高的幻觉倾向警示。真实的代价是推理常开：没有免思考模式，每次调用都在烧推理 token，简单短任务的实际成本可能比 headline 费率高。结论：对能控制 effort 档位的长上下文、高并发 Agent 负载，它是顶级性价比之选；但要为常开推理做预算，自托管前先验 HF 许可证。
— 中国吧 AI Tools Hub Editorial Team
Who Should Use MiniMax M3.1 Flash?谁适合使用MiniMax M3.1 Flash？
✓ Good Fit For适合以下场景
- High-volume agent workloads needing 1M context at $0.15/$0.60 per MTok高并发 Agent 负载：需要 100 万上下文，又想要 $0.15/$0.60 的价格
- Teams that want open weights (released 2026-10-23) for self-hosting想自托管的团队——权重已发布（2026-10-23）
- Multimodal reasoning — text, image and video inputs natively多模态推理——文本、图像、视频原生输入
✕ Not Ideal For不适合以下场景
- Simple short tasks — reasoning is always on and cannot be disabled简单短任务——推理常开、不能关闭，小任务不划算
- M3 API users who haven't updated their thinking-disabled integration老 M3 API 用户——未升级 thinking=disabled 集成会直接报错
Getting Started with MiniMax M3.1 FlashMiniMax M3.1 Flash 快速开始
1. Create an account on the MiniMax platform and get an API key在 MiniMax 平台注册账号并获取 API key2. Call the model: $0.15 input / $0.60 output per MTok, cached reads $0.015 — prices per official site调用模型：$0.15 输入 / $0.60 输出每百万 token，缓存 $0.015——价格以官网为准3. Pick one of 5 effort levels (low/medium/high/xhigh/max, default max) — thinking cannot be disabled; update old M3 integrations that parse inline <think> tags to read the reasoning_content field选 5 档 effort 之一（low/medium/high/xhigh/max，默认 max）——推理不能关闭；老 M3 集成若解析行内 <think> 标签，改为读 reasoning_content 字段Key Features核心功能
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428B MoE, ~23B Active428B MoE，约 23B 激活 — Mixture-of-experts with 428B total parameters and about 23B activated per token — near-frontier agentic scores at Flash-tier inference cost.混合专家架构：428B 总参数，每次推理仅激活约 23B，准前沿的 Agent 分数、Flash 级的推理成本。
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1M Context, 524K Output100 万上下文、524K 输出 — A 1M-token context window with up to 524,288 output tokens — whole codebases and long documents in a single run.100 万 token 上下文，输出最高 524,288 token——整个代码库、长文档，一次跑完。
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Always-On Reasoning, 5 Effort Levels推理常开，5 档 effort — Reasoning cannot be disabled; choose low, medium, high, xhigh or max (default max) per call to trade cost against intelligence.推理不能关闭；每次调用选 low/medium/high/xhigh/max（默认 max）五档之一，在成本与智能之间取舍。
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Multimodal Input多模态输入 — Native text, image and video inputs with sparse attention and a native visual encoder.原生支持文本、图像、视频输入，稀疏注意力 + 原生视觉编码器。
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Open Weights + MiniMax Sibling Apps开权重 + MiniMax 生态 — Weights released 2026-10-23 on Hugging Face and ModelScope (check the license in the official HF repo). Also by MiniMax: the AI companion app Talkie.权重已于 2026-10-23 在 Hugging Face 与 ModelScope 发布（许可证以官方 HF 仓库为准）。同为 MiniMax 出品：本站评测的 AI 陪伴应用 Talkie。
Pros & Cons优缺点
✓ Good Fit For适合以下场景
- Aggressive pricing: $0.15/$0.60 per MTok, cached $0.015 — about half of M3's standard rates激进定价：$0.15/$0.60 每百万 token，缓存 $0.015，约为 M3 标准费率的一半
- Space Bunny leaderboard pedigree — proven before the press releaseSpace Bunny 榜单血统——先登榜、后发布
- Open weights available since 2026-10-23 — self-hostable path confirmed权重自 2026-10-23 开放——自托管路径已确认
- Vendor-reported 3x speed vs M3 (200+ tokens/sec everyday use)官方称比 M3 快约 3 倍（日常 200+ token/秒）
✕ Not Ideal For不适合以下场景
- Reasoning always on — no thinking-free cheap mode for trivial tasks推理常开——琐事没有免思考的廉价模式
- Independent tests flag a high hallucination tendency — verify outputs on factual work第三方实测警示幻觉倾向较高——事实性工作要验输出
- M3 migration breaks thinking=disabled calls (HTTP 400) — integration updates needed从 M3 迁移会 break thinking=disabled 调用（HTTP 400），需升级集成
- No technical report on what changed vs M3 — upgrade story is trust-me没有对比 M3 变化的技术报告，升级故事靠信任
Use Cases应用场景
Popular ways people use MiniMax M3.1 Flash.人们使用MiniMax M3.1 Flash的常见场景：
🤖 High-Volume Agent Workloads高并发 Agent 负载
Vendor-reported 62.2 on Automation-Bench v1.0.6 and 73.7 on DeepSWE — agentic office work at $0.15/$0.60 per MTok.官方报告 Automation-Bench v1.0.6 62.2、DeepSWE 73.7——Agent 办公负载，$0.15/$0.60 每百万 token。
📚 Long-Context Reasoning长上下文推理
Whole codebases and long documents in a 1M context with up to 524K output in one pass — pick effort levels per call.整个代码库、长文档，一次装进 100 万上下文，输出最高 524K——每次调用按需选 effort 档位。
🖥️ Multimodal Apps多模态应用
Native text, image and video input with a native visual encoder — visual reasoning and document QA.原生文本、图像、视频输入 + 原生视觉编码器——视觉推理、文档问答。
🏠 Self-Hosting自托管
Weights released 2026-10-23 on Hugging Face and ModelScope (428B/23B MoE) — check the license in the official HF repository before deploying.权重已于 2026-10-23 在 Hugging Face 与 ModelScope 发布（428B/23B MoE）——部署前先确认官方 HF 仓库许可证。
Similar AI Tools相似 AI 工具
If MiniMax M3.1 Flash doesn't fit your needs, here are other popular AI tools you might consider — including its sibling app Talkie, also by MiniMax (see our full review).如果MiniMax M3.1 Flash不符合你的需求，可以看看这些热门 AI 工具——包括同为 MiniMax 出品的 Talkie（见本站完整评测）。