GPT-5.4 wins on coding (90 vs 80) and agentic desktop control. Gemini 3.1 Pro wins on research (99), context window (2M vs 272K), and price ($2 vs $2.50/1M input). GPT-5.4 is the better daily coding and reasoning tool; Gemini 3.1 Pro is the better research and large-document tool.
Pick GPT-5.4 for coding, agentic workflows, and general premium reasoning. Pick Gemini 3.1 Pro for research, large documents, and long-context analysis at a lower price.
GPT-5.4 leads on coding benchmark and adds unique computer-use capabilities — making it the stronger default for engineering and product teams.
Use GPT-5.4 if you want the strongest default. Switch only when cost, speed, or context length matters more than maximum reliability.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GPT-5.4 is the safest overall answer here when you want the strongest default instead of the lowest list price.
Grok 4 is the lower-cost option to start with when you still need useful output at scale.
Gemini 3.1 Pro is the better pick when response speed matters more than maximum reasoning depth.
GPT-5.4 leads on coding (90 vs 80) and has unique desktop-control via API.
Gemini 3.1 Pro has a 2M context window — 7× larger than GPT-5.4's 272K.
Gemini 3.1 Pro is cheaper: $2/1M input vs GPT-5.4's $2.50/1M.
Choose GPT-5.4 for coding, product reasoning, and agentic workflows.
Choose Gemini 3.1 Pro for research synthesis, large document analysis, and when context window matters most.
For writing tasks, Claude Sonnet 4.6 outperforms both.
This comparison focuses on the models most likely to answer this search intent well, not every model in the directory.
Best for agentic automation and desktop control workflows.
Best for research and deep document analysis — 2M context at the best premium price.
Use these cards as the practical decision layer: what each leading option is good at, and when it becomes the wrong default.
Best for agentic automation and desktop control workflows.
Agentic workflows, desktop automation, and complex multi-step reasoning
You need the highest coding benchmark scores — Claude Opus 4.6 and Sonnet 4.6 lead SWE-bench.
Best for research and deep document analysis — 2M context at the best premium price.
Research, deep document analysis, and long-context reasoning at competitive pricing
Your primary use case is writing quality or agentic coding — Claude wins both.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
Benchmark scores from SWE-bench (coding), ARC-AGI-2 (reasoning), and MMLU (knowledge breadth) — cross-referenced against Chatbot Arena community votes to filter out cherry-picked provider claims.
Input and output costs verified directly against each provider's official API pricing page. Updated whenever a price change is detected. Value-per-dollar is weighted separately from raw benchmark rank.
Advertised context sizes are noted but scored against real-world usability — models that degrade significantly at large contexts are penalised even if the window is technically available.
Production signals matter more than lab scores. We weight Cursor and Windsurf defaults, HackerNews sentiment, developer surveys, and which models teams actually keep using after the honeymoon period.
One-off wins on cherry-picked benchmarks don't move our rankings. We favour models that stay dependable across repeated prompts, diverse task types, and long sessions without degrading.
Time-to-first-token and output throughput from Artificial Analysis speed benchmarks. Latency is categorised from Very fast to Deliberate — relevant when building interactive or high-throughput products.
Data sources
The fastest way to see where the recommendation shifts when your priority changes.
Best for agentic automation and desktop control workflows.
Best for research and deep document analysis — 2M context at the best premium price.
Only frontier model that can control a desktop via API (click, type, navigate)
Strong at multi-step agentic tasks and autonomous workflows
Competitive coding performance with 74.9% SWE-bench score
Claude Opus 4.6 and Sonnet 4.6 outperform it on pure coding benchmarks
Smaller context window (272K) vs Gemini 3.1 Pro (2M) for research
Newsletter
Useful if you care about ranking shifts, pricing changes, or a better recommendation appearing in this decision path.
No spam. Useful updates only. Affiliate disclosures always clearly labeled.
GPT-5.4 is better for coding — it scores 90 vs Gemini 3.1 Pro's 80. For the highest coding quality, Claude Sonnet 4.6 or Opus 4.6 lead both.
Yes. Gemini 3.1 Pro scores 99 on research and leads ARC-AGI-2 reasoning. Its 2M context window is unmatched for large document analysis.
GPT-5.4 is slightly more expensive at $2.50/1M input vs Gemini 3.1 Pro's $2/1M input. Both output at around $12–15/1M tokens.
GPT-5.4 is the only frontier model with desktop computer-use via the API — it can click, type, and navigate software. Gemini 3.1 Pro doesn't have this.
Gemini 3.1 Pro wins by a large margin: 2M tokens vs GPT-5.4's 272K. If context window is the key decision factor, Gemini wins clearly.
