5 March 2025
A Breakdown of OpenAI, Anthropic, Google, and Grok Models Thus Far Available in PowerFlow
The University of Nicosia is proud to offer faculty and staff access to some of the most powerful AI models available today through its advanced Powerflow tool.
(The information in this article is accurate as of 21/02/2025)
The University of Nicosia is proud to offer faculty and staff access to some of the most powerful AI models available today through its advanced Powerflow tool. This platform grants users direct access to cutting-edge large language models (LLMs), ensuring they can leverage AI for research, education, and professional applications. More models will be added over time, always keeping up with the latest advancements in AI technology.
This post explores the latest models from OpenAI, Anthropic, Google, Grok, Groq-based and Bedrock (AWS) —highlighting their capabilities, use cases, and what makes them stand out in the field of AI.
Data for the benchmarks in this post is sourced from Artificial Analysis.
Note: We expect more powerful models to be continuously added to PowerFlow, for example GPT-o3 and Grok 3!
OpenAI
OpenAI Models (Ranked by Power)
| Model Name | Context Window | Cost (USD per 1M tokens) | Usefulness (Examples) | Benchmark Notes |
|---|---|---|---|---|
| 03-Mini | 200K tokens | Input: 1.10; Output: 4.40 | Best for deep reasoning, advanced problem-solving, complex coding, and AI research. | Highest intelligence ranking (63); strong in logic-heavy and analytical tasks. |
| GPT-o1 | 200K tokens | Input: 15.00; Output 60.00 | High-level scientific research, complex problem-solving, and in-depth coding applications. | Strong logical reasoning, but lower intelligence than o3-mini. |
| o1-Mini | 128K tokens | Input: 1.90; Output: 7.60 | Best mix of speed, reasoning, and affordability; ideal for STEM work, writing, and AI-driven projects. | Faster and cheaper than GPT-4o while offering superior intelligence. |
| GPT-4o | 128K tokens | Input: 3.00; Output: 12.00 | Best for multimodal tasks (text, images, and audio); useful for language translation and chatbots. | Good general-purpose model but not the best in raw intelligence or reasoning. |
| GPT-4o Mini | 128K tokens | Input: 0.15; Output: 0.60 | Budget-friendly AI for customer support, simple chatbots, and content generation. | More affordable than GPT-4o but significantly weaker in intelligence and reasoning. |
Which OpenAI model should you use?
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Use o3-mini for research, AI development, and complex problem-solving—it’s the most intelligent model.
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Choose GPT-o1 for scientific research and complex coding—good logic, but less intelligent than o3-mini.
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Use o1-mini for a balance of cost, speed, and reasoning—great for STEM students, writing, and AI-powered projects.
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Opt for GPT-4o if you need multimodal capabilities (e.g., image processing, language translation).
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Pick GPT-4o Mini if you want a cheap AI for basic chatbots and content generation.
Reasoning Parameter in Powerflow
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For o3-mini, GPT-o1, and o1-mini, you can specify a reasoning level of low, medium, or high.
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low: Maximizes speed and conserves tokens, but produces less comprehensive reasoning.
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medium: The default, providing a balance between speed and reasoning accuracy.
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high: Focuses on the most thorough line of reasoning, at the cost of extra tokens and slower responses.
Anthropic
Anthropic Models (Ranked by Power)
| Model Name | Context Window | Cost (USD per 1M Tokens) | Usefulness (Examples) | Benchmark Notes |
|---|---|---|---|---|
| Claude 3.7 Sonnet | 200K tokens | Input: 3.00; Output: 15.00 | The latest top-tier Claude model; excels in advanced coding, reasoning, and tasks. | Outperforms previous 3.5 Sonnet in intelligence/coding benchmarks (per new data). |
| Claude 3.5 Sonnet (NEW) | 200K tokens | Input: 3.00; Output: 15.00 | Top-performing Claude model; excels in advanced coding, reasoning, and complex tasks. | Formerly best in code generation and MMLU; now slightly behind 3.7. |
| Claude 3 Opus | 200K tokens | Input: 15.00; Output: 75.00 | Deep analytical reasoning, high-level research, advanced problem-solving. | Previously the most capable Claude, now slightly behind 3.5 Sonnet (New). |
| Claude 3.5 Sonnet | 200K tokens | Input: 3.00; Output: 15.00 | Balanced AI for content creation, translation, and general tasks. | Faster than Opus but less capable than Sonnet (New) in advanced tasks. |
| Claude 3.5 Haiku | 200K tokens | Input: 0.25; Output: 1.25 | Cost-effective, lightweight AI ideal for chatbots and summarization. | Lower power but highly affordable and efficient for simple tasks. |
Which Claude model should you use?
- Claude 3.7 Sonnet: For the absolute best coding, math, and complex reasoning tasks based on new data.
- Claude 3.5 Sonnet (New): A powerhouse if 3.7 isn’t available; excels in advanced coding and workflows.
- Claude 3 Opus: Good for in-depth analytical research and large-scale problem-solving.
- Claude 3.5 Sonnet: Ideal for balanced performance in translations, general tasks, and content creation.
- Claude 3.5 Haiku: Perfect for quick, cost-conscious tasks like chatbots and summarization.
Google Models (Ranked by Power)
| Model Name | Context Window | Cost (USD per 1M Tokens) | Usefulness (Examples) | Benchmark Notes |
|---|---|---|---|---|
| Gemini 2.0 Pro Exp | 2M tokens | Free for devs (not for production) | Best for enterprise AI, large-scale research, and deep AI applications. | Google’s most advanced Gemini model with cutting-edge capabilities. |
| Gemini 1.5 Pro (Sep) | 2M tokens | Input: 1.25; Output: 5.00 | Ideal for research papers, complex reasoning, and multi-step analysis. | High-quality AI with extensive contextual understanding. |
| Gemini 1.5 Pro (May) | 2M tokens | Input: 1.25; Output: 5.00 | Strong for legal, medical, and creative writing applications. | Slightly slower than the Sep version but strong in technical fields. |
| Gemini Exp 1206 | 2M tokens | Free for devs (experimental) | Designed for AI model testing and internal research applications. | Limited public benchmark data available. |
| Gemini 2.0 Flash | 1M tokens | Input: 0.10; Output: 0.40 | Optimized for real-time AI interactions, chatbots, and automation. | Lower power but highly efficient for fast-response applications. |
| Gemini 1.5 Flash | 1M tokens | Input: 0.07; Output: 0.30 | Best for fast, cost-effective summarization, chatbots, and automation. | High-speed performance for efficient processing. |
| LearnLM 1.5 Pro Experimental | Not available | Free for developers (experimental) | Education & learning AI, potentially optimized for tutoring and adaptive learning applications. | No public benchmark data available. |
| Gemini 2.0 Flash Lite Preview | 1M tokens | Input: 0.07; Output: 0.30 | Mobile AI assistants, compact AI models for small-scale applications. | Optimized for efficiency over power. |
Which Gemini model should you use?
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Gemini 2.0 Pro Exp: great for enterprise or large-scale academic research.
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Gemini 1.5 Pro: strong for legal, medical, and technical tasks.
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Gemini Flash variants: ideal for real-time interactions, fast automation, and cost-effective tasks.
Grok
| Model Name | Context Window | Cost (USD per 1M Tokens) | Usefulness (Examples) | Benchmark Notes |
|---|---|---|---|---|
| Grok 2 1212 | 128K tokens | Input $2.00; Output $10.00 | Suitable for advanced reasoning & creativity | No official benchmark reported |
Groq-Based Models
| Model Name | Context Window | Cost (USD per 1M Tokens) | Usefulness (Examples) | Benchmark Notes |
|---|---|---|---|---|
| Mixtral 8×7B | 32K tokens | Input: 0.24; Output: 0.24 | Good for coding support, structured Q&A, moderate reasoning | Comparable to GPT-4o or Claude 3.5 Sonnet in logic tasks but offers a smaller context window than top 128K/200K models. |
| LLaMA 3 (8B) | 8K tokens | Input: 0.05; Output: 0.1 | Basic chat, summarization, simpler coding | Similar performance range to GPT-4o Mini or Claude 3.5 Haiku. Smaller context means it’s best for shorter documents. |
| LLaMA 3 (70B) | 8K tokens | Input: 0.59; Output: 0.79 | More advanced coding & reasoning for mid-level projects | Rival to GPT-4o or Claude 3.5 Sonnet in many tasks, but still capped at 8K tokens. |
| LLaMA 3.3 (70B, 128K) | 128K tokens | Input: 0.59; Output: 0.79 | Reading lengthy academic papers, detailed Q&A | Comparable in context size to OpenAI o1-mini or Gemini Pro (up to 128K). Slightly behind top OpenAI/Anthropic models in raw intelligence. |
| LLaMA 3.1 (8B) | 8K tokens | Input: 0.05; Output: 0.08 | Lightweight tutoring or instruction-based chat | Similar to GPT-4o Mini or Claude Haiku but not suitable for large or highly complex tasks. |
| LLaMA Guard 3 (8B) | 8K tokens | Input: 0.20; Output: 0.20 | Specialized content moderation | Used alongside other models to filter harmful or biased content. |
| Qwen 2.5 (32B) | 128K tokens | Input: 0.79; Output: 0.79 | High-level coding, long-form reasoning, large input capacity | Roughly equal to GPT-4o / Claude 3.5 Sonnet in logic/coding. Comparable 128K context to mid-tier OpenAI/Anthropic. |
| DeepSeek R1 Distill Qwen 32B | 128K tokens | Input: 0.69; Output: 0.69 | Enhanced math, multi-step reasoning, advanced problem-solving | Approaches GPT-o1-level logic. Great for research or coding, but still behind o3-mini or Claude 3.7 in top-tier reasoning tests. |
Which Groq-based model should you use?
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Mixtral 8×7B: Good balance of logic and cost if you only need 32K tokens and don’t require top-tier AI intelligence.
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LLaMA 3 (8B) & 3.1 (8B): Ideal for basic chat and tutoring tasks; similar to GPT-4o Mini or Claude Haiku.
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LLaMA 3 (70B): More advanced reasoning/coding but still limited by an 8K token window.
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LLaMA 3.3 (70B, 128K): Best for long documents (128K tokens) if you need a moderate level of coding/logic.
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Qwen 2.5 (32B): Great 128K context and decent coding/logic—roughly on par with GPT-4o or Claude 3.5 Sonnet.
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DeepSeek R1 Distill Qwen 32B: Similar 128K context but with stronger math/logic, approaching GPT-o1 level for research or intricate problem-solving.
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LLaMA Guard 3 (8B): Use this for content moderation only—complements a primary model to ensure safe outputs.
Bedrock Models
| Model Name | Context Window | Cost (USD per 1M Tokens) | Usefulness (Examples) | Benchmark Notes |
|---|---|---|---|---|
| Titan Text G1 – Lite | 4K tokens | Input: 0.15; Output: 0.20 | Quick writing, summaries, generating simple documents or standard forms | Similar to GPT-4o Mini or Claude 3.5 Haiku. Note the 4K context is much smaller than many OpenAI/Anthropic/Gemini options (up to 200K). |
| Titan Text G1 – Express | 8K tokens | Input: 0.20; Output: 0.60 | Mid-range tasks: summarizing reports, assisting enterprise communication | Closer to o1-mini or Gemini Flash in complexity. The 8K context is still smaller than top models’ 128K/200K capacities. |
Which bedrock model should you use?
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Titan Text G1 – Lite: Perfect for short tasks like meeting notes, basic admin documents, or quick summaries.
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Titan Text G1 – Express: Offers more tokens (8K) and slightly stronger capabilities for enterprise-level documents and moderate summarizations, but still not meant for large research papers or heavy coding tasks compared to bigger models.
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Grok 2 1212 is currently the only Grok model in Powerflow; it offers a robust context window and moderate pricing, making it suitable for multi-turn reasoning and creative endeavors. Grok 3 will be coming soon.
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Final Top 5
Below is a concise summary of the five strongest models across OpenAI, Anthropic, Google, and Grok, chosen for their intelligence, performance, and overall capabilities:
| Model Name | Company | Context Window | Price (Approx.) | Key Strengths |
|---|---|---|---|---|
| o3-mini | OpenAI | 200K tokens | Input: $1.10 / 1M | Highest intelligence (63), excels in problem-solving, coding, and deep analytical tasks. |
| Claude 3.5 Sonnet (New) | Anthropic | 200K tokens | Input: $3.00 / 1M | Outperforms Claude 3 Opus; excels in advanced coding, reasoning, and complex tasks. |
| Gemini 2.0 Pro Exp | 2M tokens | Free (dev use) | Enterprise-grade AI with massive context window; ideal for large-scale R&D and analytics. | |
| GPT-o1 | OpenAI | 200K tokens | Input: $15.00 / 1M | Excellent for high-level research, complex coding, and intricate problem-solving. |
| o1-mini | OpenAI | 128K tokens | Input: $1.90 / 1M | Perfect blend of cost, speed, and reasoning; great for STEM and writing tasks. |
Conclusion
With access to these powerful models through the University of Nicosia’s Powerflow tool, faculty and staff can explore new frontiers in AI. Whether for research, writing, or automation, these models provide robust AI solutions tailored to a variety of needs.
Model descriptions compiled by Konstantinos Vassos
