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GPT-5.5 vs Claude Opus 4.7 vs Gemini 3.1 Pro vs Grok 4.3

Picking an AI model in May 2026 still feels like targeting something moving. Models drop every few weeks, pricing shifts without warning, and every provider publishes benchmarks that look flawless on a blog post but rarely match your actual workload.

I have been tracking these models since launch, reading release notes, checking live pricing dashboards, and watching how developers use them in production. This comparison is built from documentation and pricing pages, not vendor marketing.

As of May 23, 2026, the four frontier models are OpenAI’s GPT-5.5, Anthropic’s Claude Opus 4.7, Google’s Gemini 3.1 Pro, and xAI’s Grok 4.3. All four are capable but not interchangeable.

Short Answer

Use GPT-5.5 if you want the strongest all-around agent inside the OpenAI ecosystem. It carries multi-step tasks across coding, research, documents, spreadsheets, and computer use with less hand-holding. GPT-5.5 Instant (released May 5) now serves as the default ChatGPT model at much lower latency.

Use Claude Opus 4.7 if your hardest work is coding, long-document reasoning, careful writing, or multi-hour agentic sessions. Anthropic released it April 16 and has been iterating on Claude Code, vision resolution, and the xhigh effort tier ever since.

Use Gemini 3.1 Pro if your work lives inside Google’s world — AI Studio, Vertex AI, NotebookLM, or Workspace. It launched February 19 with Deep Think reasoning, adjustable compute budgets, and deeply competitive pricing.

Use Grok 4.3 if you want near-frontier capability at a fraction of the cost, or your workflow depends on real-time X/web search and tool calling. xAI made it generally available April 30, priced it aggressively, and positioned it as the default reasoning model while keeping Grok 4.20 for the 2M context window.

Detailed Comparison Table

What you care aboutGPT-5.5Claude Opus 4.7Gemini 3.1 ProGrok 4.3
API input price (per 1M tokens)$5.00$5.00$2.00–$2.20$1.25
API output price (per 1M tokens)$30.00$25.00$12.00$2.50
Pro tier output$180.00SameVaries by productN/A
Context window1M tokens1M tokens1M tokens1M tokens
Max output tokens128K128K64K128K
Knowledge cutoffEarly 2026Jan 2026Early 2026Dec 2025
Consumer context16K–128K1M32K–64KUp to 1M
SWE-bench Verified82.6%82.0–87.6%~80% (config dependent)~53 AA Index
GPQA Diamond~90%94.2%~88%Not disclosed
Release dateApr 23, 2026Apr 16, 2026Feb 19, 2026Apr 30, 2026
Consumer appChatGPT (Free/Go/Plus/Pro)Claude.ai (Free/Pro/Max/Team)Gemini app (Free/Pro/Ultra)Grok app, X platform
Consumer price (premium)$20–$200/mo$20–$200/mo$19.99–$124.99/3mo$16/mo+
Best useAgentic coding, Codex, research, documentsHard coding, long agents, document reasoning, writingGoogle-native multimodal, NotebookLM, Vertex AIReal-time search, cost-sensitive agents, prototyping

GPT-5.5: The OpenAI Work Loop

OpenAI launched GPT-5.5 on April 23, 2026, and followed with GPT-5.5 Instant twelve days later. The two releases together signal the strategy: GPT-5.5 is the reasoning workhorse for hard problems; GPT-5.5 Instant is the faster, cheaper default most users reach for in everyday chat.

From day one, GPT-5.5 was positioned as a model for “real work” — coding, debugging, research, data analysis, documents, spreadsheets, software operation, and tool-chaining until a task is done. On Artificial Analysis’s Coding Index, it delivers state-of-the-art intelligence at roughly half the cost of competing frontier coding models. BrowseComp scores hit 90.1% (versus Gemini’s 85.9% and Opus’s 79.3%). SWE-bench Verified sits at 82.6%, MMLU at 92.4%, and OpenAI claims a 60% reduction in hallucination rates.

API pricing runs $5 per 1M input and $30 per 1M output for standard tier, with cached input at $0.50 per 1M. GPT-5.5 Pro at $30/$180 targets maximum-capability workloads. ChatGPT Plus at $20/month gives you GPT-5.5 Thinking with 32K context; Pro at $100/month bumps you to GPT-5.5 Pro with 128K context.

Use GPT-5.5 for: Turning vague software tasks into tested implementations; research with source checking and structured output; working inside Codex on documents and spreadsheets; building agentic workflows with OpenAI’s tool ecosystem.

Watch out for: High-volume generation at $30/M output; workflows needing exact citations without verification; sensitive legal, medical, or financial tasks without human review.

Claude Opus 4.7: Careful, Difficult Work

Anthropic shipped Claude Opus 4.7 on April 16, 2026. The launch was direct about where improvements landed: advanced software engineering, complex long-running tasks, high-resolution vision, instruction following, and Claude Code workflows.

Anthropic reports 87.6% on SWE-bench Verified — the top coding leaderboard slot under their evaluation settings. On SWE-bench Pro, the harder variant, Opus 4.7 hits 64.3% versus Gemini’s 54.2% and GPT-5.5’s 58.6%. GPQA Diamond comes in at 94.2%. Vision resolution is 3.3x higher than Opus 4.6, and the new xhigh effort level uses adaptive compute for especially hard problems.

One detail worth modeling: Opus 4.7’s new tokenizer uses 1.0x to 1.35x more tokens for the same input, so effective cost can exceed what the raw pricing suggests even though listed rates stayed flat at $5 per 1M input and $25 per 1M output. Prompt caching and batch discounts offset this. Knowledge cutoff is January 2026.

Use Claude Opus 4.7 for: Reviewing complex code changes and catching subtle architecture problems; long-document analysis where tone and reasoning discipline matter; legal, finance, or enterprise writing; agentic coding through Claude Code with hook-based verification.

Watch out for: Simple tasks where Sonnet costs less; prompts calibrated for older Claude models; workflows that punish thorough, lengthy answers.

Gemini 3.1 Pro: Inside the Google Stack

Google launched Gemini 3 in November 2025 and Gemini 3.1 Pro on February 19, 2026. The update brought stronger reasoning, adjustable compute budgets, and “Deep Think Mini” — a reasoning mode that lets you dial compute up or down per problem.

Gemini’s strongest argument is distribution. If your team lives inside Workspace, Vertex AI, Search, NotebookLM, Android, or AI Studio, Gemini is not a separate tool but a layer across products you already use.

Pricing is the most aggressive on this list: $2.00–$2.20 per 1M input and $12.00 per 1M output — roughly 2.5x cheaper than GPT-5.5 or Opus 4.7 on both input and output. For SWE-bench scores near 80%, that gap reshapes high-volume economics. The consumer Gemini app caps context at 32K–64K on Pro plans; the API and AI Studio give the full 1M-token window.

Use Gemini 3.1 Pro for: NotebookLM research; Workspace-connected productivity; multimodal analysis mixing images, video, and text; Vertex AI deployments on Google Cloud; high-volume API workloads where $12/M output makes the economics work.

Watch out for: Pricing comparisons across Google surfaces without checking the exact product page; assuming the consumer app, API, and Vertex AI expose identical limits.

Grok 4.3: The Aggressive Newcomer

xAI made Grok 4.3 generally available on April 30, 2026. It is a newer pre-trained model with an improved architecture, a 1M-token context window, and a December 2025 knowledge cutoff. xAI now positions it as the default reasoning model, with Grok 4.20 retained for workloads needing the 2M-token context window.

The price is the story: $1.25 per 1M input and $2.50 per 1M output. That is 4x cheaper on input and 10x cheaper on output than GPT-5.5. Grok 4.3 lands at 53 on the Artificial Analysis Intelligence Index — above Claude Sonnet 4.6, competitive for most practical agentic and coding workflows. xAI also claims the lowest hallucination rate among current models for function-calling tasks.

Use Grok 4.3 for: Real-time research assistants with live search; cost-sensitive agentic coding and prototyping; market/news monitoring that pulls X and web data; multi-agent setups needing reliable tool calling; high-volume API workloads at $2.50/M output.

Watch out for: Assuming consumer Grok and xAI API behave identically; relying on pricing without checking the xAI console; expecting Grok 4.3 to match Opus 4.7 or GPT-5.5 on the very hardest coding benchmarks.

Benchmark Reality Check

Benchmarks are useful, but fake precision kills trust.

OpenAI reports GPT-5.5 at 88.7% SWE-bench in some configs. Anthropic reports Opus 4.7 at 87.6%. Vals AI shows GPT-5.5 at 82.6% and Opus 4.7 at 82.0% on the standard set. Different splits, different scaffolding, different prompting. None are lies, none are the full story.

A model can ace a benchmark and still produce answers that are technically correct but practically useless for your specific workflow. Your tasks have messy files, unclear requirements, weird formatting, compliance constraints, and impatient users.

The better approach is boring but reliable:

  1. Pull 20 to 50 real tasks from your actual work, including easy, normal, and failure-prone examples.
  2. Score each response for correctness, usefulness, cost, latency, and human cleanup time.
  3. Check whether the model admits uncertainty or confidently invents details.
  4. Rerun when the provider changes the model or pricing.
  5. Pick the model that saves the most total human time per dollar.

If a model only wins in demos, it is not the best model for you.

FAQ

Which AI model is actually the best in May 2026?

There is no single best. GPT-5.5 leads on broad agentic capability and ecosystem depth. Claude Opus 4.7 leads on hard coding and long-running agentic reliability. Gemini 3.1 Pro leads on price-to-performance and Google-integrated multimodal work. Grok 4.3 leads on cost-efficiency and real-time search-connected workflows.

Which model should I use for coding?

For the hardest production coding, Claude Opus 4.7 with xhigh effort in Claude Code is strongest. For speed-critical agentic coding with a broader tool ecosystem, GPT-5.5 inside Codex is competitive. For cost-sensitive coding at scale, Gemini 3.1 Pro and Grok 4.3 both deliver strong results at far lower per-token prices.

Is GPT-5.5 worth the higher output cost versus Opus 4.7?

If you depend on OpenAI’s integrated tools (Codex, Responses API, browsing, data analysis, DALL-E), GPT-5.5 is worth the premium because the integration saves development time. For API-only work without that ecosystem, Opus 4.7 delivers comparable capability at $25 vs $30 per 1M output.

Is Grok 4.3 better than Grok 4.20?

Grok 4.3 is a newer architecture with ~40% lower input pricing and is now the default reasoning model for chat, coding, and agents. Grok 4.20 stays available in the API with a larger 2M-token context window — use it if your workload demands that massive context.

How do consumer subscriptions compare?

ChatGPT Plus ($20/mo) gives GPT-5.5 Thinking with 32K context. ChatGPT Pro ($100/mo) gives GPT-5.5 Pro with 128K context. Claude Pro ($20/mo) gives Opus 4.7. Gemini Advanced ($19.99/mo) gives Gemini 3.1 Pro. Grok via X Premium+ ($16/mo) or SuperGrok. Check each provider’s current plans — pricing changes frequently.

Which One Should You Pick?

If you live in ChatGPT every day, test GPT-5.5 first. If Claude’s reasoning style already works for you, try Opus 4.7 on your hardest documents or code. If your work is inside Google’s products, Gemini 3.1 Pro is the path of least resistance. If you need live search, X data, or extremely cost-efficient API access, Grok 4.3 deserves a serious evaluation.

For teams, the answer should come from evaluation, not taste. Run the same tasks through two or three models, compare total cost including human review time, and pick the one that gets to a correct, production-ready result most efficiently.

For enterprises, include security posture, data retention, admin controls, compliance certifications, API availability, regional requirements, and vendor risk in the decision. Raw model quality is only one dimension.

Final Verdict

There is no single winner in May 2026, and honestly there should not be. Each model has a different shape, and that is good for people who need to get work done.

GPT-5.5 is the best default if you want OpenAI’s strongest workhorse across ChatGPT, Codex, and the API, especially now that GPT-5.5 Instant handles everyday tasks at lower latency.

Claude Opus 4.7 is the model to test first for difficult coding, careful writing, and long-running professional work where output quality matters more than speed or token cost.

Gemini 3.1 Pro makes the most sense when Google’s ecosystem is already part of the job, and its aggressive pricing is hard to ignore for high-volume API workloads.

Grok 4.3 is the most interesting option for cost-sensitive frontier work, real-time search, and prototyping — its pricing can dramatically change the economics of agentic AI at scale.

The safest answer is not “pick the smartest model.” It is “pick the model that produces the best verified output on your actual tasks, at a cost and risk level you can actually sustain.”

Verified Sources