Model Selection

Arcee Blitz

• Description: Arcee-Blitz (24B) is a new Mistral-based 24B model distilled from DeepSeek, designed to be both fast and efficient. We view it as a practical “workhorse” model that can tackle a range of tasks without the overhead of larger architectures.

  • #Parameters: 24B

  • Base Model: Mistral-Small-24B-Instruct-2501

  • API Access is Available via Arcee Conductor: https://conductor.arcee.ai

  • Open-source and available on Hugging Face under the Apache-2.0 license: arcee-ai/Arcee-Blitz

• Top Use Cases:

  • General-purpose task handling

  • Business communication

  • Automated document processing for mid-scale applications

Virtuoso Large

• Description: Our most powerful and versatile general-purpose model, designed to excel at handling complex and varied tasks across domains. With state-of-the-art performance, it offers unparalleled capability for nuanced understanding, contextual adaptability, and high accuracy.

  • #Parameters: 72B

  • Base Model: Qwen-2.5-72B

  • API Access is Available via Arcee Conductor: https://conductor.arcee.ai

• Top Use Cases:

  • Advanced content creation, such as technical writing and creative storytelling

  • Data summarization and report generation for cross-functional domains

  • Detailed knowledge synthesis and deep-dive insights from diverse datasets

  • Multilingual support for international operations and communications

Virtuoso Medium

• Description: A versatile and powerful model, capable of handling complex and varied tasks with precision and adaptability across multiple domains. Ideal for dynamic use cases requiring significant computational power.

  • #Parameters: 32B

  • Base Model: Qwen-2.5-32B

  • API Access is Available via Arcee Conductor: https://conductor.arcee.ai

• Top Use Cases:

  • Content generation

  • Knowledge retrieval

  • Advanced language understanding

  • Comprehensive data interpretation

Virtuoso Small

• Description: A streamlined version of Virtuoso, maintaining robust capabilities for handling complex tasks across domains while offering enhanced cost-efficiency and quicker response times.

  • #Parameters: 14B

  • Base Model: Qwen-2.5-14B

  • API access is available via Arcee Conductor: https://conductor.arcee.ai

  • Open-source and available on Hugging Face under the Apache-2.0 license: arcee-ai/Virtuoso-Small

• Top use cases:

  • General-purpose task handling

  • Business communication

  • Automated document processing for mid-scale applications

`

Coder Large

• Description: A high-performance model tailored for intricate programming tasks, Coder-Large thrives in software development environments. With its focus on efficiency, reliability, and adaptability, it supports developers in crafting, debugging, and refining code for complex systems.

  • #Parameters: 32B

  • Base Model: Qwen-2.5-32B-Instruct

  • Arcee Conductor: https://conductor.arcee.ai

• Top use cases:

  • Writing modular, reusable code across various programming languages

  • Debugging and optimizing performance in large-scale applications

  • Generating efficient algorithms for computationally intensive tasks

  • Supporting DevOps processes, such as script automation and CI/CD pipelines

Coder Small

• Description: A compact, high-performance coding model designed for efficient programming tasks, including generating code, debugging, and optimizing scripts for smaller projects.

  • #Parameters: 14B

  • Base Model: Qwen-2.5-32B-Instruct

• Top use cases:

  • Lightweight development tasks

  • Automated code reviews

  • Generating templates or prototypes quickly, code completion

Caller

• Description: Engineered for seamless integrations, Caller-Large is a robust model optimized for managing complex tool-based interactions and API function calls. Its strength lies in precise execution, intelligent orchestration, and effective communication between systems, making it indispensable for sophisticated automation pipelines.

  • #Parameters: 32B

  • Base Model: Qwen-2.5-32B

  • API Access is Available via Arcee Conductor: https://conductor.arcee.ai

• Top use cases:

  • Managing integrations between CRMs, ERPs, and other enterprise systems

  • Running multi-step workflows with intelligent condition handling

  • Orchestrating external tool interactions like calendar scheduling, email parsing, or data extraction

  • Real-time monitoring and diagnostics in IoT or SaaS environments

Maestro

• Description: An advanced reasoning model optimized for high-performance enterprise applications. Building on the innovative training techniques first deployed in maestro-7b-preview, Maestro-32B offers significantly enhanced reasoning capabilities at scale, rivaling or surpassing leading models like OpenAI’s O1 and DeepSeek’s R1, but at substantially reduced computational costs.

  • #Parameters: 32B

  • Base Model: Qwen-2.5-32B

  • API Access is Available via Arcee Conductor: https://conductor.arcee.ai

  • Hybrid training method:

    1. Warm-up (SFT Phase): Quick supervised fine-tuning phase to prime the model with high-quality reasoning exemplars.

    2. RL Optimization Phase: Utilizes Reinforcement Learning techniques, specifically designed to boost logical coherence, depth of reasoning, and accurate inference by encouraging problem-solving from fundamental principles.

• Top Use Cases:

  • Enterprise decision support systems

  • Complex analytical and logical inference tasks

  • Automated research and analysis workflows

  • Generative reasoning for technical and professional contexts