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Large AI assistants now shape how people work, learn, and search online. Four leading options today are Muse Spark, ChatGPT 5.4, Claude Opus 4.6, and Gemini 3.1 Pro. Each model focuses on slightly different strengths and pricing.
This guide explains how they compare so you can pick the right one.
These four models sit near the top of current benchmark leaderboards but differ in style and access.
Multimodal means the model can process more than one data type, for example text and images. Compute refers to the GPU or TPU processing power used to train or run the model.
A token is a piece of text, usually a few characters or a short word. The context window is the maximum number of tokens the model can read in one request.
Hybrid reasoning means the model can trade speed for more detailed thinking when needed. GDPval‑AA is a benchmark that measures performance on real knowledge work tasks.
ARC‑AGI‑2 is a benchmark that tests how well models solve new abstract logic puzzles. Humanity’s Last Exam is a graduate‑level reasoning test across many subjects.
Start a chat inside the Meta AI app or on meta.ai. Ask a direct question, for example “Explain this lab test result in simple terms,” and attach a photo of the result.
Muse Spark reads the text and image together and returns an explanation, plus extra context like risk factors or next questions for a doctor. You can then ask follow‑up questions, such as asking it to summarise the answer into a short note for family.
Muse Spark also supports shopping and social use cases. You can paste a link to a product from Instagram or Facebook and ask for pros, cons, or similar items.
For creators, you can upload a screenshot of a post and ask how different audiences may react. The model can generate captions, comments, and ideas that match the platform style.
Inside ChatGPT, select the 5.4 Thinking model when you want deeper planning. Start with a clear goal, such as “Design a four‑week study plan for Python with daily tasks.”
The model first outlines a plan, then shows the steps it will take before writing details. You can stop the thinking process and adjust the plan before it writes final content.
ChatGPT 5.4 also helps with computer use. In supported setups it can control a browser or desktop by writing scripts with tools like Playwright and by issuing mouse and keyboard actions.
Claude Opus 4.6 works well when you paste long documents or large codebases. You can upload several files, then ask for tasks such as “Map every API endpoint in this repository and list missing tests.”
Claude uses its large context window to track details over many files and will often describe its plan before giving results.
You control how deeply Claude thinks through the effort setting. High effort leads to slower but more careful reasoning, while lower effort speeds up shorter tasks. This flexibility helps when you move between quick chat and detailed analysis.
Gemini 3.1 Pro fits tasks that combine heavy reasoning with Google’s ecosystem. In the Gemini app you can ask it to “Compare three research papers on battery technology and summarise key differences in a table.”
Its strong scores on ARC‑AGI‑2 and other reasoning tests show in these multi‑step tasks.Through the Gemini API or Vertex AI, developers can connect 3.1 Pro to structured data, documents, or tools.
They can build chatbots, analysis pipelines, or NotebookLM setups that read large collections of PDFs and notes. Google AI Pro and Ultra plans raise usage limits and unlock features like Deep Research and Veo video tools around the same core model.
The table below summarises a few public, hard benchmarks where all four models have reported numbers.
GPQA is a PhD‑level science question set that tests deep factual and reasoning skill. Humanity’s Last Exam measures performance on expert‑level questions across many domains.
For coding and agentic benchmarks, GPT‑5.4 and Claude Opus 4.6 usually lead.
GPT‑5.4 scores 57.7 percent on SWE‑bench Pro, a tough software bug‑fixing benchmark, and 75 percent on OSWorld, which measures operating a computer through code.
Claude Opus 4.6 tops Terminal‑Bench 2.0, an agent coding benchmark, and leads GDPval‑AA and BrowseComp, which track knowledge work and web search tasks.
Gemini 3.1 Pro leads many abstract reasoning tests, including ARC‑AGI‑2 at 77.1 percent.
Most public benchmarks now focus on hard reasoning and real tasks, not only simple exam questions. For this comparison, the scores come from vendor blogs, benchmark leaderboards, and independent reviews that match the same named tests.
GPQA Diamond and HLE numbers come from technical write‑ups that compare Muse Spark, Gemini 3.1 Pro, GPT‑5.4, and Claude Opus 4.6 on the same settings.
Agentic workflows are setups where the model breaks a goal into steps, calls tools, and reviews its own work.
Prices here focus on consumer or small‑team access plans that unlock each model.
Prices can vary by region, currency, and time, and vendors update plans frequently. Always check the current pricing pages before you decide.
Each model offers a different core strength.
Muse Spark stands out because it aims to deliver near‑frontier performance for free inside products that billions of people already use, and it scores strongly on health and multimodal benchmarks.
ChatGPT 5.4 focuses on agent‑style computer use and broad tool support, with strong coding and knowledge work scores.
Claude Opus 4.6 sits in the middle of safety, long context, and high benchmark results, which makes it attractive for careful professional work.
Gemini 3.1 Pro leads several reasoning benchmarks and integrates closely with Google’s consumer apps and cloud platform.
Consider a realistic task: preparing for a specialist doctor appointment using lab reports and long articles.
You do not need to use all four models for every task. Instead, this example shows where each model can help in a single, complex scenario that mixes images, long text, and research.
Muse Spark, ChatGPT 5.4, Claude Opus 4.6, and Gemini 3.1 Pro all offer high‑end AI assistance, but they differ in access, strengths, and price. Muse Spark focuses on free access inside Meta’s products and shines on health and multimodal tasks.
ChatGPT 5.4 pushes forward on agents and computer use, Claude Opus 4.6 excels at long, careful reasoning, and Gemini 3.1 Pro leads several reasoning benchmarks and fits best inside Google’s stack.
Public benchmarks place Gemini 3.1 Pro near the top on ARC‑AGI‑2 and several advanced reasoning tests, with Claude Opus 4.6 and GPT‑5.4 close behind.
Muse Spark currently offers frontier‑level capability for free through the Meta AI app and meta.ai, while ChatGPT, Claude, and Gemini all have free tiers with lower limits or older models.
GPT‑5.4 and Claude Opus 4.6 both perform well on coding and agent benchmarks like SWE‑bench Pro and Terminal‑Bench 2.0, while Gemini 3.1 Pro also scores well on coding tests and integrates tightly with Google’s developer tools.
A very large context window matters when you work with big codebases or long document sets; for short chats and everyday tasks, smaller windows are often enough.
Match the model to your main environment and tasks: Meta apps and health content suggest Muse Spark, heavy coding and agents suggest ChatGPT 5.4 or Claude Opus 4.6, and deep reasoning inside Google’s ecosystem suggests Gemini 3.1 Pro.
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