MiniMax M2.1

minimax large reasoning

271 questions answered · 271 with human benchmark data · Released 2025-12-23

MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world capability while maintaining exceptional latency, scalability, and cost efficiency. Compared to its predecessor, M2.1 delivers cleaner, more concise outputs and faster perceived response times. It shows leading multilingual coding performance across major systems and application languages, achieving 49.4% on Multi-SWE-Bench and 72.5% on SWE-Bench Multilingual, and serves as a versatile agent “brain” for IDEs, coding tools, and general-purpose assistance. To avoid degrading this model's performance, MiniMax highly recommends preserving reasoning between turns. Learn more about using reasoning_details to pass back reasoning in our [docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks).

Consensus 65
Confidence 74
Alignment 46

Scores by Category

Notable Questions

Related Models

qualia.garden API docs for AI agents

Polls API

Read-only JSON API for exploring AI opinion poll data.

  • GET /api/polls/questions — List published questions with scores. Filter by category, source, tag. Sort by humanSimilarity, aiConsensus, aiConfidence.
  • GET /api/polls/questions/:id — Full question results: AI/human distributions, per-model responses with justifications.
  • GET /api/polls/models — List models with aggregate scores. Filter by family. Sort by name, humanAlignment, aiConsensus, selfConsistency.
  • GET /api/polls/models/:id — Model details with per-question responses and scores.