Beyond Leaderboards: Tokenomics of Agentic Small Language Model Ensembles

arXiv:2610.00954 · cs.CL · Submitted 2026-10-01 · Read on arXiv

cs.CL

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Accuracy — 55× in this paper · explained in 1 episode
• Benchmark — 13× in this paper · explained in 2 episodes
• Large Language Model — 8× in this paper
• Small Language Model — 8× in this paper
• Model Context Protocol — 5× in this paper
• Robustness — 5× in this paper · explained in 5 episodes
• Agentic AI — 3× in this paper · explained in 1 episode
• Fidelity — 3× in this paper · explained in 2 episodes
• Agentic Workflows — 2× in this paper · explained in 1 episode
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Agentic AI systems — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Model Context Protocol (MCP) — 1× in this paper · explained in 8 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Sample Complexity — 1× in this paper · explained in 15 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Small Language Models are the Future of Agentic AI
• FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
• Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference
• SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
• AgentBench: Evaluating LLMs as Agents
• GAIA: a benchmark for General AI Assistants
• Evaluating LLM Metrics Through Real-World Capabilities
• Small Language Models (SLMs) Can Still Pack a Punch: A survey (updated 2026)
• Instruction-Following Evaluation for Large Language Models

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