Artificial Intelligence: Top AI Tools to Revolutionize Your Life
The AI Model Showdown: Who’s Leading the Race in 2025?
The rapid evolution of Artificial Intelligence has sparked a competitive race among organizations to develop the most advanced AI models. From reasoning and coding to mathematics and language skills, these models are setting new benchmarks. Today, we’ll explore the top-performing AI contenders, their standout features, and the organizations driving innovation in 2024.
The Top Contenders
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OpenAI
- Global Average: 75.67
- Strengths:
- Reasoning: 91.58 (Best in class!)
- Mathematics: 80.32
- Coding: 69.69
- Why it stands out:
OpenAI continues to lead with its exceptional models. Known for their superior reasoning and complex problem-solving capabilities, this model is a top choice for tasks requiring logical precision and mathematical expertise.
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Google’s gemini
- Global Average: 61.83
- Strengths:
- Mathematics: 69.03
- Data Analysis: 68.11
- Why it stands out:
Google’s Gemini series excels in data-driven tasks, with a strong focus on mathematics and data analysis, making it a go-to for researchers and analysts.
-
DeepSeek’s v3
- Global Average: 60.45
- Strengths:
- Coding: 61.77
- Data Analysis: 60.94
- Why it stands out:
Emerging as a competitive player, DeepSeek is carving a niche in coding and data analysis, offering solid support for developers and data professionals.
The Top Contenders at a Glance:
| Model | Organization | Global Average | Reasoning Average | Coding Average | Mathematics Average | Data Analysis Average | Language Average | IF Average |
|---|---|---|---|---|---|---|---|---|
| llama-3.3-70b-instruct-turbo | Meta | 50.16 | 50.75 | 36.59 | 42.24 | 49.49 | 39.20 | 82.67 |
| gemini-2.0-flash-exp | 59.26 | 59.08 | 54.36 | 60.39 | 61.67 | 38.22 | 81.86 | |
| o1-2024-12-17 | OpenAI | 75.67 | 91.58 | 69.69 | 80.32 | 65.47 | 65.39 | 81.55 |
| gemini-exp-1121 | 57.36 | 49.92 | 49.75 | 63.75 | 60.29 | 40.30 | 80.15 | |
| gemini-2.0-flash-thinking-exp-1219 | 61.83 | 64.58 | 53.13 | 69.03 | 68.11 | 36.83 | 79.32 | |
| gemini-1.5-flash-002 | 48.59 | 47.00 | 41.87 | 47.63 | 48.35 | 27.92 | 78.76 | |
| gemini-exp-1206 | 64.09 | 57.00 | 63.41 | 72.36 | 63.16 | 51.29 | 77.34 | |
| meta-llama-3.1-405b-instruct-turbo | Meta | 52.36 | 53.25 | 42.65 | 41.05 | 55.85 | 45.46 | 75.90 |
| deepseek-v3 | DeepSeek | 60.45 | 56.75 | 61.77 | 60.54 | 60.94 | 47.48 | 75.25 |
| gemini-1.5-flash-exp-0827 | 45.21 | 46.33 | 40.35 | 30.60 | 51.40 | 29.60 | 72.97 | |
| gemini-1.5-pro-002 | 54.33 | 49.08 | 48.80 | 59.07 | 54.97 | 43.29 | 70.78 | |
| gemini-1.5-flash-8b-exp-0924 | 36.01 | 23.75 | 28.67 | 31.66 | 42.28 | 19.13 | 70.55 | |
| gemini-1.5-flash-8b-exp-0827 | 36.67 | 35.00 | 28.74 | 28.12 | 37.32 | 20.80 | 70.02 | |
| grok-2-1212 | xAI | 54.30 | 54.83 | 46.44 | 54.88 | 54.45 | 45.58 | 69.63 |
| grok-beta | xAI | 49.18 | 37.00 | 45.15 | 45.84 | 54.27 | 43.16 | 69.62 |
| claude-3-5-sonnet-20241022 | Anthropic | 59.03 | 56.67 | 67.13 | 52.28 | 55.03 | 53.76 | 69.30 |
| gemini-1.5-pro-exp-0827 | 53.29 | 50.92 | 41.43 | 58.50 | 53.50 | 46.15 | 69.26 | |
| meta-llama-3.1-70b-instruct-turbo | Meta | 44.89 | 43.00 | 33.49 | 34.72 | 53.75 | 35.42 | 68.98 |
| gpt-4o-2024-08-06 | OpenAI | 55.33 | 53.92 | 51.44 | 49.54 | 60.91 | 47.59 | 68.58 |
| gpt-4o-2024-05-13 | OpenAI | 54.41 | 49.67 | 50.00 | 46.98 | 61.57 | 50.05 | 68.21 |
| learnlm-1.5-pro-experimental | 52.19 | 43.42 | 46.87 | 57.77 | 54.97 | 41.98 | 68.16 | |
| claude-3-5-sonnet-20240620 | Anthropic | 58.74 | 57.17 | 60.85 | 54.32 | 58.87 | 53.21 | 68.01 |
| mistral-large-2411 | Mistral AI | 48.43 | 43.50 | 47.08 | 42.55 | 50.15 | 39.39 | 67.93 |
| amazon.nova-pro-v1:0 | Amazon | 43.55 | 32.58 | 38.15 | 38.14 | 48.31 | 36.96 | 67.13 |
| chatgpt-4o-latest-0903 | OpenAI | 51.66 | 50.50 | 47.44 | 42.45 | 57.93 | 45.30 | 66.37 |
| o1-mini-2024-09-12 | OpenAI | 57.76 | 72.33 | 48.05 | 61.99 | 57.92 | 40.89 | 65.40 |
| gpt-4o-2024-11-20 | OpenAI | 52.19 | 55.75 | 46.08 | 42.87 | 56.15 | 47.37 | 64.94 |
| qwen2.5-72b-instruct-turbo | Alibaba | 51.44 | 45.42 | 57.64 | 54.29 | 51.91 | 34.99 | 64.39 |
| claude-3-opus-20240229 | Anthropic | 49.12 | 40.58 | 38.59 | 43.36 | 57.89 | 50.39 | 63.89 |
| mistral-large-2407 | Mistral AI | 48.31 | 41.67 | 47.08 | 44.69 | 53.16 | 39.52 | 63.73 |
| claude-3-5-haiku-20241022 | Anthropic | 43.45 | 28.08 | 51.36 | 35.54 | 48.45 | 35.37 | 61.88 |
| gpt-4-turbo-2024-04-09 | OpenAI | 50.40 | 50.92 | 49.00 | 43.02 | 54.36 | 44.26 | 60.85 |
| olmo-2-1124-13b-instruct | AllenAI | 22.09 | 16.33 | 10.41 | 13.51 | 20.60 | 11.16 | 60.56 |
| gemini-1.5-pro-001 | 44.22 | 37.00 | 32.31 | 40.33 | 55.07 | 40.36 | 60.24 | |
| command-r-plus-04-2024 | Cohere | 27.11 | 20.58 | 19.46 | 17.99 | 25.48 | 19.70 | 59.47 |
| qwen2.5-coder-32b-instruct | Alibaba | 46.23 | 42.08 | 56.85 | 46.61 | 49.87 | 23.25 | 58.69 |
| deepseek-v2.5-1210 | DeepSeek | 45.98 | 40.17 | 46.09 | 51.60 | 48.45 | 31.14 | 58.40 |
| gemma-2-27b-it | 38.19 | 28.08 | 35.95 | 26.52 | 47.87 | 32.62 | 58.10 | |
| command-r-plus-08-2024 | Cohere | 31.76 | 24.75 | 19.14 | 21.27 | 38.06 | 29.73 | 57.61 |
| gpt-4-0125-preview | OpenAI | 45.71 | 47.17 | 41.80 | 32.05 | 56.83 | 39.22 | 57.19 |
| gpt-4o-mini-2024-07-18 | OpenAI | 41.26 | 32.75 | 43.15 | 36.31 | 49.96 | 28.61 | 56.80 |
| mistral-small-2402 | Mistral AI | 28.36 | 19.17 | 21.18 | 19.92 | 34.59 | 18.89 | 56.40 |
| command-r-08-2024 | Cohere | 27.31 | 21.92 | 17.90 | 18.36 | 33.34 | 16.72 | 55.62 |
| claude-3-haiku-20240307 | Anthropic | 33.85 | 26.33 | 24.46 | 23.37 | 44.47 | 29.13 | 55.32 |
| meta-llama-3.1-8b-instruct-turbo | Meta | 25.97 | 13.33 | 18.74 | 18.31 | 32.82 | 17.71 | 54.90 |
| amazon.nova-lite-v1:0 | Amazon | 36.35 | 36.67 | 27.46 | 36.70 | 37.23 | 25.93 | 54.13 |
| mistral-small-2409 | Mistral AI | 33.39 | 29.92 | 25.74 | 24.25 | 42.73 | 24.49 | 53.23 |
| gemma-2-9b-it | 28.66 | 15.17 | 22.46 | 19.80 | 36.39 | 25.53 | 52.62 | |
| gemini-1.5-flash-001 | 39.22 | 34.25 | 34.31 | 32.59 | 49.87 | 31.71 | 52.58 | |
| mixtral-8x22b-instruct-v0.1 | Mistral AI | 32.45 | 26.33 | 32.03 | 26.57 | 35.67 | 21.81 | 52.32 |
| qwen2.5-7b-instruct-turbo | Alibaba | 34.90 | 28.42 | 38.37 | 39.49 | 35.22 | 15.80 | 52.11 |
| amazon.nova-micro-v1:0 | Amazon | 29.56 | 25.08 | 20.18 | 34.35 | 33.95 | 15.78 | 48.04 |
| phi-3-small-8k-instruct | Microsoft | 24.03 | 15.92 | 20.26 | 17.58 | 30.29 | 12.94 | 47.20 |
| phi-3-mini-128k-instruct | Microsoft | 22.36 | 20.50 | 15.04 | 15.72 | 34.69 | 9.15 | 39.08 |
| phi-3-mini-4k-instruct | Microsoft | 22.08 | 26.83 | 15.54 | 14.96 | 30.21 | 8.56 | 36.36 |
| qwq-32b-preview | Alibaba | 39.90 | 57.71 | 37.20 | 56.21 | 31.62 | 21.09 | 35.59 |
Specialized Strengths
-
Best in Coding:
Anthropic’s claude-3-5-sonnet-20241022 takes the crown with a 67.13 in coding—perfect for developers tackling complex programming tasks. -
Best in Mathematics:
OpenAI’s o1-2024-12-17 impresses with an 80.32, ideal for solving intricate mathematical challenges. -
Best in Language:
OpenAI’s o1-2024-12-17 and Anthropic’s claude-3-opus-20240229 shine in natural language understanding with scores of 65.39 and 50.39, respectively. -
Best in Inference (IF):
Meta’s llama-3.3-70b-instruct-turbo leads with an 82.67, excelling at drawing logical conclusions and efficient decision-making.
The Underdogs Worth Watching
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AllenAI’s olmo
- Global Average: 22.09
- Why it’s interesting:
A work in progress, it reminds us that innovation often starts small.
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Microsoft’s phi
- Global Average: 22.08
- Why it’s interesting:
A lightweight model, it offers potential for simpler tasks and edge computing applications.
Key Takeaways
- OpenAI and Google dominate the leaderboard with versatile, high-performing models.
- Meta and DeepSeek are strong in inference and coding, respectively.
- Anthropic and Alibaba excel in specialized domains like coding and mathematics.
- The landscape is diverse, offering tailored solutions for reasoning, coding, data analysis, and more.
The Road Ahead
The AI race is driving innovation at an unprecedented rate. As models grow increasingly specialized and capable, their applications will continue to expand across industries. Whether you’re a developer, a data scientist, or simply curious about AI, there’s something to look forward to in this ever-evolving space.
We Want to Hear from You!
Which AI model do you think will shape the future? Are there specific features or improvements you’d like to see? Share your thoughts in the comments below!
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