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

MiniMax M2.7 transforms OpenClaw into a superior AI agent platform. Discover SWE-Pro benchmarks, seamless OAuth setup, cost savings vs Claude, advanced tips, and real-world agent workflows.

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