MiniMax: MiniMax M2.1

Description

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).

Raw fields snapshot

{
  "id": "minimax/minimax-m2.1",
  "canonical_slug": "minimax/minimax-m2.1",
  "name": "MiniMax: MiniMax M2.1",
  "display_name": "MiniMax: MiniMax M2.1",
  "provider": "minimax",
  "description": "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.\n\nCompared 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.\n\nTo 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).",
  "context_length": null,
  "source_type": "model_only",
  "best_rank": null,
  "pricing": {
    "prompt": null,
    "completion": null
  },
  "pricing_summary": {},
  "capabilities": {
    "modalities": [
      "text"
    ],
    "context_length": null,
    "architecture": {
      "modality": "text->text",
      "input_modalities": [
        "text"
      ],
      "output_modalities": [
        "text"
      ],
      "tokenizer": "Other",
      "instruct_type": null
    }
  },
  "__detail_source": "model_snapshot",
  "__raw_snapshot": {
    "model": {
      "id": "minimax/minimax-m2.1",
      "slug": "minimax/minimax-m2.1",
      "display_name": "MiniMax: MiniMax M2.1",
      "provider": "minimax",
      "description": "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.\n\nCompared 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.\n\nTo 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).",
      "context_length": null,
      "modalities": [
        "text"
      ],
      "tags": [],
      "source_type": "model_only",
      "updated_at": "2026-03-01T02:42:38.190323+00:00",
      "source": "model_only"
    },
    "overall_score": null,
    "best_rank": null,
    "ranks_by_category": {},
    "scores_by_category": {},
    "pricing_summary": {},
    "capabilities": {
      "modalities": [
        "text"
      ],
      "context_length": null,
      "architecture": {
        "modality": "text->text",
        "input_modalities": [
          "text"
        ],
        "output_modalities": [
          "text"
        ],
        "tokenizer": "Other",
        "instruct_type": null
      }
    }
  }
}