GPT-4.1 versus its peers: Gemini 2.5 Pro and Llama 4 Maverick
- Philip Moses
- Apr 21
- 2 min read
Updated: 6 days ago
As AI continues to evolve, three powerful models are leading the charge: GPT-4.1 from OpenAI, Gemini 2.5 Pro from Google, and LLaMA 4 Maverick from Meta. Each of these models brings unique strengths, from advanced reasoning to multimodal capabilities and real-time performance.

In this blog, we’ll dive into how these models stack up in key areas like vision handling, speed, tool integrations, and user experience. By the end, you’ll know exactly which model is best suited to your needs in the fast-moving world of AI.
Model Overview
GPT-4.1 (OpenAI)
Available via ChatGPT and API
High accuracy and consistency
Excels in creative writing, coding, and logical reasoning
Gemini 2.5 Pro (Google DeepMind)
Integrated with Google ecosystem (Docs, Sheets, etc.)
Strong in real-world knowledge and advanced logic
Supports multimodal input, including video
LLaMA 4 Maverick (Meta)
Open-source and highly customizable
Lightweight and optimized for smaller environments
Suitable for developers who want control over deployment
Model | Context Window (Tokens) |
|
|
|
|
|
|
All three models support large context windows, allowing them to process long documents and codebases. LLaMA 4 Maverick leads in this area.
🧠 Benchmark Performance

HellaSwag tests commonsense reasoning.
MMLU covers diverse subjects like law, math, and science.
⚙️ Technical Specifications
Feature | GPT-4.1 | Gemini 2.5 Pro | LLaMA 4 Maverick |
| Proprietary | Proprietary | Mixture-of-Experts (128 experts) |
| Not disclosed | Not disclosed | ~22T tokens (public + Meta data) |
| Text, Images | Text, Images, Video | Text, Images, Video (early fusion) |
| No | No | Under LLaMA 4 Community License |
🧑💻 Use Case Comparison
Model | Best For |
| Software development, research, logic-heavy applications |
| Business workflows, document processing, multimodal applications |
| Custom deployments, open-source projects, multilingual or light setups |
Cost and Efficiency
GPT-4.1: High performance but resource-heavy. Paid access only (ChatGPT Plus or API).
Gemini 2.5 Pro: Integrated and optimized for enterprise use within Google Cloud. May require paid tiers for full access.
LLaMA 4 Maverick: Free, open-source, and highly adaptable. Best option for low-cost, on-premise solutions.
Final Thoughts
Each model brings unique advantages:
Choose GPT-4.1 for top-tier reasoning, coding, and multi-domain tasks.
Choose Gemini 2.5 Pro for long-form data processing and advanced logic, especially within Google’s ecosystem.
Choose LLaMA 4 Maverick if you need a flexible, cost-efficient, and customizable open-source option.
The best model depends on your specific needs — context length, compute resources, licensing constraints, and integration preferences.
Comments