The AI landscape in 2025 has transformed dramatically with the emergence of powerful new models from OpenAI, Anthropic, Google DeepMind, and xAI. This comprehensive analysis compares the latest AI models across five critical performance dimensions: language understanding, coding capabilities, reasoning power, mathematical problem-solving, and multimodal processing.
Comprehensive Performance Comparison Table
| Model | MMLU (Lauguage) |
Coding | Reasoning | Math | Multimodal | Context Window | Price |
| GPT-4o | 82% | HumanEval: 87.2% | - | - | Text, Audio, Image, Video | - | - |
| GPT-4.1 | 90.2% | SWE-Bench: 54.6% | GPQA: 66.3% | AIME 2024: 48.1% | Supported | 1M tokens | Input $2/Output $8 |
| GPT-o3 | ~92% (est.) | SWE-Bench Leader | Top-tier Reasoning | AIME: 96.7% | Supported | - | High |
| GPT-o4-mini | 82% | HumanEval: 87.2% | GPQA: 81.4% | AIME 2024: 93.4% | Supported | 200K tokens | Low |
| GPT-o4-mini-high | 82% | HumanEval: 87.2%+ | Enhanced Reasoning | AIME: 93.4%+ | Supported | 200K tokens | Medium |
| Grok 3 | 92.7% | HumanEval: 86.5% | GPQA: 84.6% | AIME 2025: 93.3% | Limited | 1M tokens | X Premium+ |
| Grok 3 (Think) | 92.7%+ | 86.5%+ | Maximum Performance | 93.3%+ | Limited | 1M tokens | X Premium+ |
| Claude 3.7 Sonnet | 86% | SWE-Bench: 62.3% | GPQA: 78.2% | AIME 2024: 61.3% | Supported | 200K tokens | Output $15 |
| Claude 3.7 (Deep) | 86% | SWE-Bench: 70.3% | GPQA: 84.8% | AIME: 80% | Supported | 200K tokens | High |
| Gemini 2.5 | 78% (est.) | HumanEval: 71.5% | Strong | MGSM: 75.5% | Supported | - | Medium |
| Gemini 2.5 Pro | 85.8% | SWE-Bench: 63.8% | GPQA: 84% | AIME 2024: 92% | Top-tier | 1M+ tokens | Input $3.44 |
Key Takeaways: The AI Performance Matrix
Before diving deep, here's what you need to know about the current AI model hierarchy:
- Best Overall Performance: Gemini 2.5 Pro leads in multimodal tasks and mathematical reasoning
- Top Coding Model: Claude 3.7 Sonnet dominates with 70.3% on SWE-Bench
- Strongest Reasoning: OpenAI's o3 and Gemini 2.5 Pro share the crown
- Most Cost-Effective: GPT-o4-mini delivers premium performance at budget prices
- Best for Real-time Knowledge: Grok 3 with X/Twitter integration
Language Understanding: Breaking the 90% Barrier
The battle for language comprehension supremacy has reached new heights, with multiple models crossing the prestigious 90% threshold on the MMLU benchmark:
Top Performers
- Grok 3: 92.7% (Current leader)
- GPT-4.1: 90.2% (First to break 90%)
- Gemini 2.5 Pro: 85.8%
- Claude 3.7 Sonnet: 86% (with extended thinking)
- GPT-o4-mini: 82.0% (Best among lightweight models)
What makes these scores remarkable is that they approach or exceed human expert performance across 57 academic disciplines. Grok 3's massive computational investment has paid off, setting a new standard for knowledge comprehension.
Coding Revolution: When AI Becomes the Developer
The coding capabilities of modern AI have evolved from simple script generation to complex software engineering tasks:
Code Generation Champions
- Claude 3.7 Sonnet: 70.3% on SWE-Bench Verified (GitHub issue resolution)
- GPT-o4-mini: 87.2% on HumanEval (Lightweight champion)
- Grok 3: 86.5% on HumanEval
- Gemini 2.5 Pro: 63.8% on SWE-Bench
- GPT-4.1: 55% on SWE-Bench (Strong on HumanEval ~85%)
Claude 3.7's "deep thinking" mode proves invaluable for debugging, while GPT-o4-mini delivers enterprise-grade coding at a fraction of the cost.
Reasoning Power: The Intelligence Test
Complex reasoning separates true AI intelligence from pattern matching. Here's how models fare on the most challenging tests:
GPQA Diamond (Graduate-level Questions)
- Gemini 2.5 Pro: 84.0%
- Claude 3.7 Sonnet: 84.8% (with deep thinking)
- Grok 3: 84.6%
- GPT-o3-mini: 79.7%
- GPT-4.1: 66.3%
Humanity's Last Exam (HLE)
- Gemini 2.5 Pro: 18.8% (Current leader)
- OpenAI o3: ~20% (Research model)
- GPT-4.1: 9.8%
These scores might seem low, but HLE represents the pinnacle of human knowledge—questions that challenge even domain experts.
Mathematical Mastery: Where Numbers Meet Intelligence
Mathematics reveals an AI's true reasoning capabilities:
AIME 2024/2025 Performance
- Gemini 2.5 Pro: 92.0% (AIME 2024)
- OpenAI o3: 87.3%
- Grok 3: 89.3% (GSM8K), 83.9% (AIME)
- Claude 3.7 Sonnet: 61.3%
- GPT-4.1: 48.1%
Gemini 2.5 Pro's mathematical dominance stems from its extensive chain-of-thought processing, though this comes at a higher computational cost.
Multimodal Processing: Beyond Text
The ability to process images, audio, and video alongside text defines next-generation AI:
Multimodal Leaders
- Gemini 2.5 Pro: 81.7% on MMMU (Supports text, image, audio, video)
- GPT-4.1: Strong vision capabilities with 1M token context
- GPT-o4-mini: 59.4% on multimodal reasoning
- Claude 3.7 Sonnet: Limited multimodal support
- Grok 3: Basic image processing capabilities
Cost-Performance Analysis: ROI for Enterprises
Understanding the price-performance ratio is crucial for business adoption:
Best Value Models
- GPT-o4-mini: $0.15/$0.60 per million tokens (input/output)
- Claude 3.7 Sonnet: $3/$15 per million tokens
- GPT-4.1: $2/$8 per million tokens
- Gemini 2.5 Pro: ~$3.44 per million tokens (blended)
- Grok 3: Available through X Premium+ subscription
Specialized Use Cases: Choosing the Right Model
For Software Development
- Enterprise Projects: Claude 3.7 Sonnet
- Budget-Conscious Teams: GPT-o4-mini
- Frontend Development: GPT-4.1 or Claude 3.7
For Research and Analysis
- Scientific Computing: Gemini 2.5 Pro or OpenAI o3
- Literature Review: GPT-4.1 (1M token context)
- Real-time Data: Grok 3
For Creative Tasks
- Multimodal Content: Gemini 2.5 Pro
- Text Generation: GPT-4.1 or Claude 3.7
- Cost-Effective Creation: GPT-o4-mini
Future Trends and Predictions
The AI model landscape reveals several emerging patterns:
- Deep Thinking Integration: All major providers now offer "thinking" modes
- Specialized vs. General Models: Task-specific optimization gaining ground
- Cost Efficiency Revolution: Lightweight models matching heavyweight performance
- Multimodal Convergence: Text-only models becoming obsolete
- Tool Integration: AI models leveraging external capabilities
Conclusion: The Multi-Model Future
No single AI model dominates all categories. Success in 2025 requires a strategic approach:
- Use Gemini 2.5 Pro for complex multimodal tasks and mathematics
- Deploy Claude 3.7 Sonnet for transparent reasoning and debugging
- Leverage GPT-4.1 for large-scale document processing
- Utilize GPT-o4-mini for cost-effective daily operations
- Engage Grok 3 for real-time knowledge and STEM applications
The future belongs to organizations that can effectively orchestrate multiple AI models, matching specific capabilities to business needs while optimizing for cost and performance.
Last updated: May 4, 2025. Benchmark data compiled from official releases and third-party evaluations.
