American Invitational Mathematics Examination (AIME) 2024 problems.

AIME-2024

A smaller model optimized for fast, cost-efficient reasoning. Achieves remarkable performance for its size and cost, particularly in math, coding, and visual tasks. It is the best-performing benchmarked model on AIME 2024 and 2025, with significantly higher usage limits than o3.

o4-mini

Third-generation Qwen model featuring hybrid reasoning capabilities that can switch between thinking and non-thinking modes. Trained on 36 trillion tokens (double that of Qwen2.5), with support for 119 languages and dialects. Available in 6 dense models (0.6B to 32B parameters) and 2 MoE models (30B/3B active and 235B/22B active).

Qwen-3

The o1 model series is trained with large-scale reinforcement learning to reason using chain-of-thought. OpenAI o1 is the next model in this series (previously OpenAI o1-preview), with advanced reasoning capabilities that provide new avenues for improving safety and robustness. The model can reason about safety policies in context when responding to potentially unsafe prompts, through deliberative alignment.

Anthropic's most intelligent model to date and the first hybrid reasoning model on the market. Claude 3.7 Sonnet can produce near-instant responses or extended, step-by-step thinking that is made visible to the user. API users have fine-grained control over how long the model can think for (up to 128K tokens). Priced at $3 per million input tokens and $15 per million output tokens at launch, including thinking tokens.

Claude 3.7 Sonnet

DeepSeek-R1 is a first-generation reasoning model trained via large-scale reinforcement learning. Built on DeepSeek-V3-Base, it incorporates cold-start data before RL to address challenges like endless repetition and poor readability found in DeepSeek-R1-Zero. Achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks through advanced chain-of-thought reasoning capabilities.

DeepSeek-R1

A powerful Mixture-of-Experts (MoE) language model with 671B total parameters and 37B activated for each token. Features Multi-head Latent Attention (MLA) and DeepSeekMoE architectures with innovative auxiliary-loss-free load balancing and multi-token prediction training. Pre-trained on 14.8T high-quality tokens with only 2.788M H800 GPU hours.

DeepSeek-V3

A research preview of OpenAI's largest and most capable GPT model to date. GPT-4.5 represents a significant advancement in scaling unsupervised learning, delivering broader world knowledge, dramatically reduced hallucinations (37.1% vs 61.8% for GPT-4o), and enhanced emotional intelligence for more natural human collaboration. Excels at creative tasks, writing assistance, and complex problem-solving with improved factual accuracy and nuanced understanding of user intent.

Rank	Model	Provider	Score	Parameters	Released	Type
1	o4-mini	OpenAI	93.4		2025-04-16	Multimodal
2	Qwen-3	Alibaba	85.7	235B (22B active)	2025-04-29	Text
3	o1	OpenAI	83.3		2024-09-12	Multimodal
4	Claude 3.7 Sonnet	Anthropic	80		2025-02-24	Multimodal
5	DeepSeek-R1	DeepSeek	79.8	671B (37B activated)	2025-01-20	Text
6	DeepSeek-V3	DeepSeek	39.2	671B total, 37B activated	2024-12-26	Text
7	GPT-4.5	OpenAI	36.7		2025-02-27	Multimodal

AIME-2024

AIME-2024 Leaderboard

About AIME-2024

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AIME-2025

AIME

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