MiniMax-M2.7

OpenRouter's listing explicitly names MiniMax-M2.7 with a release date of Mar 18, 2026, a 205K-token context window, and headline benchmarks: 56.2% on SWE-Pro, 57.0% on Terminal Bench 2, and a 1495 ELO on GDPval-AA, framed as a next-generation LLM designed for autonomous, real-world productivity and continuous improvem The same page positions M2.7 for production-grade workflows including live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. Pricing metadata is shown ($0.24/$0.96 per 1M tokens at a 60% promotional rate, plus a weighted-average effective input of $0.13

Opper AI's release tracker explicitly names MiniMax M2.7 as a dated entry in the MiniMax M-series release history, placing its launch on 18 March 2026 with a 197K context window, $0.25/$1.00 per million input/output token pricing, and an Intelligence score of 39 (per Artificial Analysis, cross-checked against vendor an The M2.7 entry on Opper's tracker is a single line among seven MiniMax releases, so it offers thin technical substance: no architecture details, no benchmark breakdown, and no developer-facing guidance. Pricing and intelligence figures are sourced from Artificial Analysis rather than MiniMax's own documentation, so the

The release of MiniMax M2.7 adds enhancements to the popular MiniMax M2.5 model, built for agentic harnesses, and other complex use cases in fields such as…

MINIMAX-W (00100.HK), a domestic large model company, announced that its MiniMax M2.7 has been officially open-sourced globally. Together with...

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LangChain benchmarks show GLM-5 and MiniMax M2.7 now rival Claude and GPT on agent tasks while cutting costs from $250/day to $12/day for high-volume applications

当 AI 开始自我演进，懂复盘、会纠错、能演进！MiniMax M2.7 震撼实测：从复杂逻辑推理到 Three.js 动力学引擎，它的工程交付能力如何？302.AI 基准实验室对比实测，揭秘其如何从“生成工具”跃迁为“参与交付”的硬核 Agent。点击查看深度测评，领略这款高性价比“数字员工”的进阶实力。, 📊MiniMax-M2.7核心亮点：从执行到闭环优化🚀专业工程能力的

InferenceX publishes a third-party technical profile of the MiniMax-M2 series that explicitly names MiniMax-M2.7 alongside M2.5. The page documents M2.7's 2026-03-18 release, the dual serving variants "MiniMax-M2.7" and "M2.7-highspeed," and the underlying MoE architecture (230B total parameters, ~10B active, 62 layers The same profile reports an internal M2.7 version that autonomously optimized a programming scenario and surfaces positioning focused on agentic tool use, coding, and productivity workflows. The page is not itself a MiniMax announcement but cites MiniMax's M2.7 announcement page and API release notes for the 2026-03-18

The Together AI model listing for MiniMax M2.7 restates concrete benchmark numbers and capability claims attributed to the model itself, independent of any host-specific SLA or availability marketing. It reports SWE-Pro at 56.22% (matching GPT-5.3-Codex), 55.6% on VIBE-Pro (near Opus 4.6) for end-to-end Web/Android/iOS The same page describes M2.7's self-evolution workflow: an internal version ran 100+ autonomous optimization rounds — analyzing failure trajectories, modifying code, evaluating results, and deciding to keep or revert — to achieve a 30% improvement on internal programming benchmarks, while during training the model upda

A third-party deep-dive on MiniMax M2.7, updated March 2026, consolidates figures from the official March 18, 2026 technical report and frames M2.7 as a self-improving model for complex agent harnesses, tool-chain coordination, and multi-stage productivity tasks. The page reports concrete engineering-benchmark scores: The same deep-dive emphasizes that M2.7's core value is delivery reliability under messy production constraints, not just stronger coding output, making it useful as a continuous optimization component in model and harness development operations. For engineering managers evaluating the model, the aggregated benchmark s

April 13, 2026: GitHub launches remote control for Copilot CLI sessions from web and mobile, MiniMax releases M2.7 open-source with day-0 vLLM support, the Qwen3.5-Omni API becomes available internationally, and Gemini 3.1 Flash Live takes the lead in the τ-Voice voice leaderboard.