Frontier Models

Frontier models are the cutting-edge AI systems that push the boundaries of what artificial intelligence can do. At any point in time, these are the models that achieve the highest scores on challenging benchmarks, handle the most complex reasoning tasks, and demonstrate the broadest range of capabilities. As of early 2025, frontier models include OpenAI's GPT-4o and o1/o3 series, Anthropic's Claude 3.5 Opus, Google's Gemini 1.5/2.0 Pro, and Meta's Llama 3.1 405B.

What distinguishes frontier models from mid-tier or budget models is their performance on hard tasks — tasks that require genuine reasoning, nuanced understanding, or multi-step problem solving. On easy tasks like simple classification or basic question answering, the difference between frontier and mid-tier models may be small. On hard tasks like complex math, advanced coding, scientific analysis, or long-context reasoning, frontier models pull significantly ahead. This is where their larger size, better training data, and more sophisticated alignment techniques pay off.

Frontier models come with tradeoffs. They are the most expensive to use, both in API pricing and in computational requirements for self-hosting. They tend to have higher latency than smaller models. Access may be restricted or rate-limited. And their capabilities, while impressive, are not uniformly superior — a frontier model might excel at reasoning but be outperformed by a specialized smaller model on specific narrow tasks like code completion or translation.

The frontier is constantly moving. New model releases every few months reset what "state of the art" means. Yesterday's frontier model becomes today's mid-tier option as new models launch. GPTCrunch tracks these changes in real time, helping you understand which models currently represent the frontier, how they compare to each other, and whether a less expensive model might meet your needs. For many applications, a model that was frontier six months ago — now available at a fraction of the cost — delivers more than enough capability.