# Haiku 4.5 vs MiniMax M2.1: Comparative Analysis of Agent Task Benchmark Tests

> Jesutofunmie's open-source comparative evaluation project systematically tested the performance of Anthropic Haiku 4.5 and MiniMax M2.1 models on Agent tasks, revealing differences in their design thinking and execution skills in multi-round workflows, and providing data references for developers to select appropriate Agent models.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-05T03:15:18.000Z
- 最近活动: 2026-04-05T03:25:33.187Z
- 热度: 159.8
- 关键词: Haiku, MiniMax, Agent评测, 模型对比, 多轮对话, 工具调用, Anthropic, AI基准测试
- 页面链接: https://www.zingnex.cn/en/forum/thread/haiku-4-5-vs-minimax-m2-1-agent
- Canonical: https://www.zingnex.cn/forum/thread/haiku-4-5-vs-minimax-m2-1-agent
- Markdown 来源: floors_fallback

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## Haiku4.5 vs MiniMax M2.1 Agent Task Benchmark: Core Insights

Jesutofunmie's open-source comparison project systematically tested Anthropic Haiku4.5 and MiniMax M2.1 on Agent tasks, revealing their differences in design thinking and execution skills. This provides valuable data references for developers to select suitable Agent models, covering dimensions like task understanding, tool usage, and multi-round dialogue.

## Evaluation Background & Model Overviews

Traditional benchmarks (MMLU, HumanEval) fail to assess Agent-specific capabilities (multi-round dialogue, tool calling, error recovery). Thus, the Haiku-4.5-vs-Minimax-2.1 project was launched.
- **Haiku4.5**: Lightweight Claude model, fast/low-cost, improved reasoning, suitable for latency/cost-sensitive scenarios.
- **MiniMax M2.1**: Optimized for Agent tasks (Function Calling, multi-round management), strong in Chinese context. Both are widely used for Agent construction.

## Evaluation Methodology

Systematic methods ensure comparability:
**Task Design**: Info collection, tool usage, planning/decomposition, error recovery, multi-round coordination.
**Metrics**: Task completion rate, efficiency (rounds/tools/tokens), quality (accuracy/completeness), user experience, error handling.
**Control Variables**: Same prompt, tools, token budget, timeout, evaluation standards.

## Key Findings: Design Thinking vs Execution Skills

**Haiku4.5**: Strong design thinking—deep task understanding, strategy planning, structured output, boundary awareness. Limitations: Conservative tool usage, occasional goal forgetting, weaker Chinese adaptation.
**MiniMax M2.1**: Strong execution—proactive tool usage, stable multi-round state, fast response, native Chinese advantage. Limitations: Surface-level task understanding, shallow planning, fluctuating output quality.

## Scenario-Based Model Selection

**Choose Haiku4.5**: Demand analysis, content generation (reports), multi-language scenarios, cost-sensitive deployment.
**Choose MiniMax M2.1**: Tool-intensive tasks, Chinese-priority apps, real-time interaction, long-process tasks.

## Hybrid Strategy Insights

Combining models yields better results:
- Layered: Haiku (planning) + MiniMax (execution)
- Routing: Design tasks → Haiku, execution → MiniMax
- Collaboration: Two Agents complement strengths (increases complexity but boosts capability).

## Limitations & Future Directions

**Limitations**: Limited vertical domain coverage (medical/legal/finance), subjective metrics (user experience), outdated results as models update, single benchmark limitations.
**Future**: Expand task diversity, add more models (GPT-4/Claude3), automated continuous evaluation, real user feedback validation.

## Industry Significance & Conclusion

**Industry Value**: Provides systematic Agent evaluation methodology, highlights 'design vs execution' divide, suggests future Agent systems may need combined specialized models.
**Conclusion**: Haiku excels in design/structure; MiniMax in execution/Chinese. Choose based on scenario needs, not just benchmarks—monitor model updates and validate in real scenarios.