marco-o1

marco-o1

Open-source model with advanced reasoning chains
2024-11-13
LLM
Input:
$0.2/1M tokens
Output:
$0.2/1M tokens
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API Overview

Marco-o1 is AIDC-AI’s flagship reasoning-optimized language model, primarily positioned as a professional-grade AI problem-solving engine that combines “high-level reasoning chains with robust logical inference.”

  • Specialized in complex reasoning: Deeply optimized for math, code, science, and logic tasks, delivering outstanding performance in authoritative benchmarks.
  • Reasoning-chain compression technology: Significantly reduces the number of inference steps while maintaining high accuracy, enhancing response efficiency and readability.
  • Long-context support: Natively supports ultra-long inputs, making it ideal for applications such as paper parsing, multi-hop question answering, and complex document reasoning.
  • Ready for structured output: Supports JSON Schema and Function Calling, facilitating seamless integration into agents or automated systems.
  • Developer-friendly and open-source: Offers clear usage guidelines and deployment instructions, enabling quick integration with mainstream inference frameworks.

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Core Capabilities

🧠 Deep problem decomposition: Can think step by step like a human expert, progressively solving highly complex, composite problems.

🧮 Dual strengths in math and code: Demonstrates stable and verifiable reasoning paths in tasks such as algebra, geometry, and algorithm design.

🔍 Precise context utilization: Efficiently extracts key information from long texts, enabling cross-paragraph correlation and logical integration.

🧰 Seamless agent collaboration: Natively adapts to tool calls and structured responses, easily integrating into professional workflows in research, engineering, and other fields.

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API Analytics

API Reference (1)

API DescriptionAPI EndpointRequest MethodStabilityParameter Description
Marco-o1
POST
Stable
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API Pricing

$
ModelDescriptionContextOfficial Price302.AI Price

marco-o1

-
32000

Input$0.2 / 1M tokens
Output$0.2 / 1M tokens

Input$0.2/ 1M tokens
Output$0.2/ 1M tokens
Original Price