ChatGPT 5.5 (GPT-5.5) Release: Features, Benchmarks, Pricing & Claude Opus 4.7 Comparison

On April 23, 2026, OpenAI released "ChatGPT 5.5 (GPT-5.5)." Billed by OpenAI itself as "a new class of intelligence for real work and AI agents," the model posted 82.7% on Terminal-Bench 2.0, pulling well ahead of Anthropic's Claude Opus 4.7 (69.4%) and Google's Gemini 3.1 Pro (68.5%) and reclaiming SOTA (state of the art) on 14 benchmarks in the process.

At the same time, the API list price doubled compared to GPT-5.4 ($5/$30 per MTok), and Claude Opus 4.7 still beats it on SWE-Bench Pro. The honest read is "the strongest, but not the universal best." There's also a documented tendency to answer confidently about things it doesn't actually know — something to be careful about in medical, legal, or regulated work.

Drawing on OpenAI's official release, the OpenAI Developer Docs, and several independent benchmark reports, this article gives you the full breakdown: what's new, the benchmarks, pricing, plan availability, how it stacks up against Claude and Gemini, and how to pick the right model for what you're doing.

1. Release Overview — Date, Availability, Spec Sheet

2. What's New — 5 Key Improvements

1. A Base Model Retrain (Reportedly the First Since GPT-4.5)

Several write-ups describe GPT-5.5 as the first base model retrain since GPT-4.5, saying GPT-5 through 5.4 were refinements of the same base. OpenAI's announcement itself does not say this, so it cannot be confirmed from an official source.

2. Better Token Efficiency

According to OpenAI's announcement, GPT-5.5 keeps the same per-token latency as GPT-5.4 while reaching equal or better results with fewer tokens, and Codex was tuned so most users need fewer tokens than with GPT-5.4. The announcement gives no reduction figure (the widely quoted "about 40%" came from third-party measurement). The list price doubled, but because fewer tokens are used, total cost can rise by less than 2x.

From OpenAI co-founder Greg Brockman (TechCrunch):

"It's a model that thinks faster and sharper with fewer tokens — that kind of model, compared to something like 5.4."

3. ~1M Context Window (API)

The API version expands to 1,050,000 tokens (~1M). The Codex integration is 400K. Just remember the metered surcharge: prompts above 272K tokens incur 2x input and 1.5x output pricing, so very long-context workloads need a cost model.

4. Five-Level Reasoning Effort Control

The API exposes reasoning.effort with five settings:

• none: no reasoning (fastest, cheapest)
• low: light reasoning
• medium: default (balanced)
• high: deep reasoning (complex tasks)
• xhigh: maximum reasoning (slowest and most expensive, highest accuracy)

This mirrors the output_config.effort knob on Claude Opus 4.7, and the industry as a whole is converging on "let the caller dial reasoning depth."

5. Expert-SWE at 73.1% — Handles 20-Hour-Class Tasks

On OpenAI's newly published internal eval Expert-SWE (extremely complex coding tasks with a median 20-hour human completion time), GPT-5.5 hit 73.1% — up 4.6 points from GPT-5.4's 68.5%. That's a big jump for long-running autonomous coding agent reliability.

3. Benchmarks — Head-to-Head With Claude and Gemini

Bottom Line: GPT-5.5 Leads 14 Benchmarks, Claude 6, Gemini 2

Counting the 22 rows in OpenAI's published evaluation table that include a Claude Opus 4.7 or Gemini 3.1 Pro score, GPT-5.5 (including Pro) leads 14, Claude Opus 4.7 leads 6, and Gemini 3.1 Pro leads 2 (our count; rows with only Opus 4.6 scores excluded). GPT-5.5 comes out ahead on most comparable rows.

That said, on SWE-Bench Pro (production-grade coding tasks), Claude Opus 4.7 still wins at 64.3% vs GPT-5.5's 58.6%. For coding work, splitting models by task is still worth doing.

Third-Party Verification: CodeRabbit Code Review Eval

Independent code review service CodeRabbit reports the following GPT-5.5 improvements:

• Curated benchmark: expected issue detection 58.3% → 79.2%, precision 27.9% → 40.6%
• Real-world dataset: issue detection 55.0% → 65.0%, precision 11.6% → 13.2%

CodeRabbit's read: "the model prefers local changes, preserves behavior, and tends to focus on actual failure points." Translation — instead of sweeping rewrites, it leans toward targeted, accurate fixes.

4. GPT-5.5 vs GPT-5.5 Pro — Which Should You Use?

How to Choose

• Pick standard GPT-5.5: general coding, writing, agent workloads, cost-conscious use
• Pick GPT-5.5 Pro: math and scientific research, paper drafting, complex decision-making — accuracy over cost

5. Pricing — Why the 2x Hike?

API Pricing (Standard GPT-5.5)

Why the 2x Hike?

OpenAI hasn't directly explained the price increase, but the likely drivers are:

1. Cost of a base model retrain — reportedly the first ground-up rebuild since GPT-4.5
2. Pricing in performance gains — significant improvements on Terminal-Bench and others
3. Token efficiency offsets some of the pain — using fewer tokens partially balances the higher unit price

The effective cost increase depends on how many fewer tokens you use. If output dropped 40%, it would be "2x x 0.6 = 1.2x" (40% is not an official figure, so measure on your own tasks). For input-heavy tasks (summarization, analysis), you take the full 2x hit head-on — keep that in mind.

6. ChatGPT Plan Availability

At Launch, Free Users Couldn't Use GPT-5.5

At launch, GPT-5.5 wasn't available on the Free plan, whose default model was GPT-5.3 Instant. On May 5, 2026, GPT-5.5 Instant became the default model for all users. GPT-5.5 Thinking required Plus ($20/mo) or higher.

7. API Specs and Developer Features

Supported Features

• Function calling
• Structured outputs (JSON Schema)
• Streaming
• Reasoning effort control (none/low/medium/high/xhigh)
• Tools: web search, file search, image generation, Code Interpreter, Hosted Shell, Apply Patch, Skills, Computer Use, MCP, Tool Search
• Fine-tuning: not supported at launch
• Audio / video in or out: not supported

Rate Limits at launch (Tier 5: highest)

• RPM (requests per minute): 15,000
• TPM (tokens per minute): 40,000,000
• Batch queue limit: 15,000,000,000

Note as of October 12, 2026: The figures above are for Tier 5 at launch. On October 6, 2026, OpenAI simplified its API usage tiers from five to three: Build, Launch and Grow. According to its rate limits guide, an organization moves up automatically once its total credit purchases reach $5, $100 and $500, and on the top tier, Grow, Astra, Sol and Terra get 15,000 RPM and 40,000,000 TPM. The new table has no row for GPT-5.5, so check your own organization's limits under Settings > Organization > Limits.

Reasoning Effort Example (Python)

from openai import OpenAI
client = OpenAI()

response = client.responses.create(
    model="gpt-5.5",
    reasoning={"effort": "high"},  # none/low/medium/high/xhigh
    input="Solve this complex math problem step by step..."
)

print(response.output_text)

8. Codex Integration and the Super-app Strategy

Codex Fast Mode

Alongside the GPT-5.5 release, Codex gained a Fast Mode:

• 1.5x faster processing
• 2.5x the cost (in credits)

The Super-app Strategy

According to TechCrunch, Brockman described GPT-5.5 as a step toward a "super app" that bundles "ChatGPT + Codex + AI browser" into one offering. The plan is to deliver these as a single enterprise package — what OpenAI calls "a step toward more agentic, more intuitive computing."

Conceptually, this is the "all-in-one package to maximize developer experience" pattern from PaaS like Vercel or Next.js, brought into the AI agent space.

9. GPT-5.5 vs Claude Opus 4.7 vs Gemini 3.1 Pro

How to Choose

• Best overall + cutting-edge agent performance — GPT-5.5 (especially if >$30/MTok output is acceptable)
• Long autonomous coding and safety-first work — Claude Opus 4.7 (wins on SWE-Bench Pro and has cheaper output pricing)
• Google Workspace integration and multimodal — Gemini 3.1 Pro

10. The Catch — Watch Out for Overconfidence

Citing results from Artificial Analysis's AA-Omniscience (which measures factual accuracy and whether a model abstains when it doesn't know), several write-ups flagged a tendency in GPT-5.5 to "answer confidently about things it doesn't actually know."

In short: high accuracy, but also a high rate of wrong answers where it should have said "I don't know."

High-Risk Use Cases

• Medical diagnosis or prescriptions — wrong information can be life-threatening
• Legal advice or case research — citing hallucinated cases is a professional ethics issue
• Financial advice or tax work — regulatory exposure
• Citations in academic writing — known cases of citing non-existent papers

Mitigations

1. Mandatory fact-checking — never use AI output as-is; verify against primary sources
2. Use the web search tool — make the model fetch real-time information
3. Cross-check against Claude Opus 4.7 — for accuracy-critical work, run answers past multiple models
4. Tell it to say "I don't know" — instruct via system prompt: "if uncertain, say so explicitly"

11. When to Pick GPT-5.5 — By Use Case

Pick GPT-5.5 When

• Long-running autonomous coding agents — Expert-SWE 73.1% (OpenAI's internal eval, up from GPT-5.4's 68.5%)
• PC automation / Computer Use — OSWorld 78.7% is on par with Opus 4.7
• Customer support automation — Tau2-bench 98.0% is essentially perfect
• Advanced math and scientific research — FrontierMath T4 35.4% (well above Opus 4.7's 22.9%)
• You're committed to the OpenAI ecosystem — integrates with ChatGPT and Codex

Skip GPT-5.5 When

• SWE-Bench Pro–level production coding — Claude Opus 4.7 still leads
• Accuracy-critical work (medical, legal, financial) — watch out for hallucinations
• Cost is the top priority — $30/MTok output is at the high end
• You want a free option — not available on the Free plan
• Audio or video processing — text + image input only

FAQ

Q1. When did GPT-5.5 become available in ChatGPT?

April 23, 2026 (US time), on the Plus, Pro, Business, and Enterprise plans. GPT-5.5 Pro is limited to Pro, Business, and Enterprise.

Q2. Can I use GPT-5.5 on the Free plan?

Not at launch (the default was GPT-5.3 Instant). From May 5, 2026, GPT-5.5 Instant became the default for all users, but GPT-5.5 Thinking required at least the $20/mo Plus plan.

Q3. GPT-5.5 vs Claude Opus 4.7 — which is better?

Overall, GPT-5.5 (it leads 14 rows of OpenAI's evaluation table vs Claude's 6). But on SWE-Bench Pro, Claude Opus 4.7 wins 64.3% to 58.6% — so for production-grade coding, Claude has the edge. Claude is also cheaper on output ($25/MTok vs GPT-5.5's $30/MTok).

Q4. The API got more expensive — how do I keep costs under control?

Yes, $5/$30 per MTok is 2x GPT-5.4. But it needs fewer tokens than GPT-5.4, so the real cost increase can be less than 2x (OpenAI gives no reduction figure, so measure on your own tasks). Cost control tips:
1. Use Batch API / Flex (50% discount)
2. Use cached input ($0.50/MTok, 1/10 of regular)
3. Use reasoning.effort=low for lighter tasks
4. Avoid prompts above 272K tokens

Q5. What's actually different about GPT-5.5 Pro?

It has stronger reasoning, with notable score lifts on complex math (FrontierMath: 35.4% → 39.6%) and scientific research tasks. The catch is the price — 6x the API rate ($30 input / $180 output). Outside research and serious paper-writing use cases, the price/performance often doesn't pencil out.

Q6. Is fine-tuning supported?

No (the model page lists fine-tuning as "Not supported").

Q7. Anything to watch out for when using the 1M context?

Prompts above 272K tokens trigger a surcharge of 2x input and 1.5x output across the entire session. If you're designing an API around 1M-token usage, run the cost numbers up front.

Q8. What's GPT-5.5's knowledge cutoff?

December 1, 2025. Anything after that (Jan 2026 onward) isn't in training data, so the web search tool is effectively required for current information.

Q9. Are hallucinations any better?

Citing Artificial Analysis's AA-Omniscience, write-ups note that "accuracy is high, but so is its tendency to answer confidently about things it doesn't know." OpenAI claims safety improvements officially, but for medical, legal, or financial work, fact-checking remains mandatory.

Q10. Will my existing GPT-5 app just work?

API compatibility is preserved — switching the model ID from gpt-5 to gpt-5.5 is enough to migrate. That said, taking advantage of new features (like the reasoning.effort levels from none to xhigh, or specifying the Pro variant ID) is worth a design pass.

Wrapping Up: GPT-5.5 Is the Strongest, but Not the Universal Best

GPT-5.5 holds SOTA on 14 benchmarks and pulls clearly ahead of Claude Opus 4.7 and Gemini 3.1 Pro to reclaim the industry top spot. It's especially strong on agent tasks, PC automation, long-running autonomous coding, and math and scientific research.

At the same time, it still loses to Claude Opus 4.7 on SWE-Bench Pro, shows a "confident hallucination" tendency, and comes with a 2x API price hike — so it's not an unconditional win.

The smarter play is "pick the right one — GPT-5.5, Claude Opus 4.7, or Gemini 3.1 Pro — for the task at hand." All-in on the OpenAI ecosystem? GPT-5.5. Long coding sessions and safety-first work? Claude. Google Workspace integration? Gemini. Multi-model operations are becoming the 2026 standard.

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