In 2025, the AI landscape is packed with powerful new models: OpenAI’s GPT-4o (including a lightweight “mini” version), Anthropic’s Claude 4 Opus, Google’s Gemini 2.5 Pro, and DeepSeek’s cutting-edge R1 model. Each platform pushes the limits of speed, intelligence, and special capabilities. Developers and enthusiasts now have more choice than ever. Below we compare their key strengths, updated specs, and ideal use cases.
OpenAI’s GPT-4o (the “omni” model) is now the default in ChatGPT. Its new “mini” variant is optimized for speed and cost. Despite its smaller size, GPT-4o mini retains full multimodal abilities (handling text, images, audio, even video). It matches GPT-4’s fluency while cutting latency and cost. In benchmarks, GPT-4o mini achieves exceptional scores in math and coding. For example, with tool use it scored 99.5% pass@1 on the AIME math exam. This makes it great for quick data analysis, coding assistance, and interactive applications that need fast response times.
OpenAI also released GPT-4.1 mini, a version even stronger at following instructions and coding compared to the original mini model. In everyday use, GPT-4o mini shines in general Q&A, conversational chat, and multimodal tasks (like captioning images or understanding speech). It’s very accessible: GPT-4o replaced the older GPT-4, so anyone using ChatGPT or OpenAI’s API gets these improvements automatically. In short, GPT-4o mini is ideal for quick, cost-efficient reasoning and creative assistance across text, audio, and visual inputs.
Claude 4 Opus is Anthropic’s new flagship model, designed to excel at software engineering and complex logic. Anthropic highlights that Opus 4 is “the world’s best coding model,” easily outperforming previous models on coding benchmarks (it achieved 72.5% on SWE-Bench). Unlike many models that burn out after a few thousand tokens, Claude 4 Opus can maintain focus over very long documents. It can work for hours on end, handling multi-file codebases and continuous workflows without losing its place. This makes it ideal for large-scale development projects, automated debugging, and any scenario where the AI needs to think deeply and persistently.
Claude 4 also introduced advanced tool and memory features. It can use multiple tools in parallel (like web search or code runners) and even create “memory files” to store facts over time. For example, developers saw Claude Opus automatically build step-by-step notes while performing a task. In practical terms, Claude 4 Opus is best when you need an AI to manage multi-step problems, maintain context across long sessions, or provide thorough code edits. It’s the go-to for heavy coding and reasoning jobs. (Anthropic’s lighter Sonnet 4 model offers improved performance too, but Opus 4 is the standout for the toughest tasks.)
Google’s Gemini 2.5 Pro is a breakthrough on scale: it offers a 1,000,000-token context window, far larger than any other model. This means it can analyze books, entire datasets, or full-length videos all at once. Gemini 2.5 Pro is optimized for complex tasks, and in testing it now leads coding-focused leaderboards (like the WebDev Arena) and tops the Hugging Face LLM Arena on user preference. Google notes that developers love 2.5 Pro for coding, and its new “DeepThink” mode allows it to solve very hard problems (for example, it scored highest on a difficult math olympiad test). In short, Gemini 2.5 Pro is unmatched for projects that need huge memory and advanced reasoning.
This model is fully multimodal, with improvements in audio and video. It can write code, explain concepts, and even generate natural-sounding audio output. Google emphasizes its educational abilities: after training with learning science experts, Gemini 2.5 Pro outperforms other models on tutoring and teaching tasks. In practical use, Gemini is well-suited for large enterprise or research problems: think of analyzing multi-hour video meetings, generating long reports, building complex multi-step applications, or tutoring students on deep subjects. It’s also available through Google Cloud’s Vertex AI and other platforms, ensuring broad access. Essentially, Gemini 2.5 Pro is the all-around champion for massive tasks and multi-domain intelligence.
DeepSeek is a new Chinese AI startup that released the DeepSeek-R1 model in early 2025. R1 is an open-weight model (its parameters are public) trained heavily with reinforcement learning for reasoning. DeepSeek reports that R1 offers reasoning comparable to GPT-4 at a tiny fraction of the cost. In benchmarks, DeepSeek-R1 achieved about 90.8% on MMLU (a tough general knowledge test) and 97.3% on a complex math set. It also excelled at code contests, outperforming 96% of human participants on Codeforces challenges. Remarkably, DeepSeek did this with far less compute: they trained R1 with about one-tenth the computing power usually required. All this suggests DeepSeek-R1 is a very efficient and capable model.
Because DeepSeek is open and efficient, it’s great for research and teams on a budget. Use cases include math problem-solving, logical puzzles, and data analysis where you want transparency and customization. The R1 model shines in structured tasks (complex logic, mathematics, and code) and is freely available to developers under an MIT license. In short, DeepSeek R1 is a high-performance open alternative: you can run it locally or via OrionAI for free, tweak it for your needs, and rely on it for heavy reasoning tasks without the expense of other models.
| Model | Context Window | Notable Strengths |
|---|---|---|
| GPT-4o Mini (OpenAI) | Up to ~128K tokens | Fast multimodal reasoning (text, vision, audio); excellent at math and coding with tools |
| Claude 4 Opus (Anthropic) | Up to 200K tokens | Best-in-class coding and long-horizon tasks; runs hours-long workflows with memory support |
| Gemini 2.5 Pro (Google DeepMind) | 1,000K tokens | Massive context and multimodal intelligence; tops coding and learning tasks with experimental “Deep Think” |
| DeepSeek-R1 (DeepSeek) | ~16K tokens | Open-source reasoning expert; strong at math/coding contests with low resource use |
Each model has its sweet spot. For example:
- Everyday Chat & Multimodal Tasks: GPT-4o Mini is agile and works great with images or audio, making it ideal for general Q&A, translation, or quick creative brainstorming.
- Large-Scale Coding & Dev Workflows: Claude 4 Opus shines at complex software projects — automated pair programming, code refactoring, or any task requiring sustained analysis over many files.
- Big Data & Advanced Reasoning: Gemini 2.5 Pro is perfect for problems needing huge memory (long reports, video scripts, or intensive learning tasks), plus it leads on coding challenges and academic benchmarks.
- Open Research & Math Problems: DeepSeek R1 is great for research scenarios where you want an open model. It excels at math and logical tasks and runs efficiently on modest hardware.
Ultimately, the best choice depends on your needs. Luckily, OrionAI makes it easy to experiment with all of them. OrionAI’s platform offers free support for GPT-4o, Claude, Gemini, and DeepSeek models. Check out our latest product update to see how multi-model support works and what’s new.
We also provide helpful tools like the Gemini CLI Guide, which walks you through using Google’s Gemini models from the command line. Give these models a spin on OrionAI and see which one fits your project!