GPT-5.5

Overview

GPT-5.5 is OpenAI’s frontier large language model released on April 23, 2026 (codename “Spud”). It is a proprietary cloud model for complex professional work: agentic coding, multi-step tool use, research, document and spreadsheet creation, computer use, and long-horizon tasks where the model plans, acts, checks itself, and continues without constant hand-holding. Product home and announcement: openai.com/index/introducing-gpt-5-5. API model page: developers.openai.com/api/docs/models/gpt-5.5.

GPT-5.5 sits above GPT-5.4 in the GPT-5 line and was the public flagship at launch for coding and “real work on a computer.” By mid-2026 OpenAI also ships later ChatGPT reasoning lines (for example GPT-5.6 Sol / Terra / Luna on the ChatGPT pricing matrix), so buyers should treat GPT-5.5 as a named model family with Instant, Thinking, Pro, and specialized variants—not as the only model in the product forever. Successor branding does not erase GPT-5.5: the API still lists gpt-5.5 and gpt-5.5-pro with published rates and snapshots.

You reach GPT-5.5 three main ways: (1) ChatGPT (web, mobile, desktop)—GPT-5.5 Thinking rolled out to Plus, Pro, Business, and Enterprise at launch; GPT-5.5 Pro to Pro, Business, and Enterprise; GPT-5.5 Instant became the default chat model for all users on May 5, 2026; (2) Codex, OpenAI’s coding-agent suite (CLI, IDE, cloud, desktop), with GPT-5.5 available on Go through Enterprise/Edu plans and a published 400K context window in Codex; (3) the OpenAI API (gpt-5.5, gpt-5.5-pro, snapshot gpt-5.5-2026-04-23), available from April 24, 2026 after OpenAI delayed API day-one for extra safeguards.

Key features

• Agentic coding — OpenAI positions GPT-5.5 as its strongest agentic coding model to date. Official launch scores include 82.7% on Terminal-Bench 2.0 (vs 75.1% for GPT-5.4), 58.6% on SWE-Bench Pro public, and higher Expert-SWE (internal long-horizon coding) than GPT-5.4, often with fewer tokens and retries. Early partners (Cursor, NVIDIA, product startups) highlighted persistence, conceptual clarity, and tool reliability in long sessions.
• Long-horizon tool use — Designed to plan messy multi-part tasks, call tools, recover from errors, and keep going. Supports web search, file search, code interpreter, hosted shell, apply-patch, skills, computer use, MCP, and tool search on the Responses API path.
• Large context & output caps (API) — Documented 1,050,000 context window, 128,000 max output tokens, knowledge cutoff Dec 01, 2025. Prompts with more than 272K input tokens are billed at 2× input and 1.5× output for the full session (standard, batch, and flex).
• Reasoning effort control — API reasoning.effort supports none, low, medium (default), high, and xhigh. Higher effort spends more compute for harder problems; community cost analyses often find xhigh is where GPT-5.5’s premium over GPT-5.4 is most justified.
• GPT-5.5 Pro — Same underlying model with parallel test-time compute for higher accuracy and more comprehensive answers. Stronger on hard research and math slices in OpenAI’s tables (for example BrowseComp and FrontierMath Tier 4), slower and much more expensive in the API.
• GPT-5.5 Instant — Latency-optimized default for ChatGPT everyday chat (rolled out May 5, 2026, replacing GPT-5.3 Instant). Emphasizes lower hallucination on high-stakes law/medicine/finance prompts, better personalization via past chats/files/connectors, and Instant-tier speed—not a drop-in for full Thinking/Pro agent runs.
• Codex integration — In Codex, GPT-5.5 is the agent model for implementation, refactors, debugging, testing, and validation, with optional Fast mode (~1.5× token generation for ~2.5× cost). OpenAI reports significantly fewer tokens to complete the same Codex tasks vs GPT-5.4 while matching per-token latency in real serving.
• Knowledge work & computer use — Strong GDPval (wins/ties 84.9%), OSWorld-Verified (78.7%), Tau2-bench Telecom (~98% without prompt tuning in OpenAI’s write-up), plus internal finance and office-style evals. Fits research synthesis, spreadsheets, decks, and multi-app workflows when paired with computer-use tools.
• Scientific / technical research loop — Gains on GeneBench and BixBench-style multi-stage analysis; early academic testers (e.g. Ethan Mollick) described near–early-PhD quality drafts from short prompt chains with literature that was real rather than fabricated—still jagged on novelty and taste.
• Multimodal I/O (API) — Text + image input; text output. Audio and video not supported on the gpt-5.5 model card. Streaming, function calling, and structured outputs supported; fine-tuning not supported.
• Snapshots & endpoints — Pin gpt-5.5-2026-04-23 for stability. Responses and Chat Completions are the primary paths; rate limits scale by usage tier (Free tier: not supported for this model; Tier 1 starts 500 RPM / 500k TPM).
• Safety stack & cyber variants — System card describes OpenAI’s strongest safeguards to date at launch, High-capability posture for cyber and bio risk categories, external red-teaming, and ~200 early-access partners. Separate paths: standard GPT-5.5, GPT-5.5 with Trusted Access for Cyber (TAC), and limited-preview GPT-5.5-Cyber for vetted defensive security teams.

Pricing

There is no single “GPT-5.5 subscription.” You pay via ChatGPT / Codex plan usage (subscription allotments) or via the API (pay-per-token). Figures below are USD list rates from OpenAI’s API docs and launch blog as of mid-2026; tax, currency, and promos vary. Always re-check API pricing and ChatGPT pricing.

API token rates (per 1M tokens)

Model	Input	Cached input	Output	Notes
gpt-5.5	$5.00	$0.50	$30.00	Standard short-context rates. ~2× GPT-5.4’s $2.50 / $15.
gpt-5.5 long context	$10.00	$1.00	$45.00	Sessions with >272K input tokens (full session uplift).
gpt-5.5-pro	$30.00	—	$180.00	Highest accuracy; long-context doubles to $60 / $270.
Batch / Flex	~50% off	—	~50% off	Launch blog: half standard rate for Batch and Flex.
Priority processing	~2.5×	—	~2.5×	Higher priority serving when available.

Regional processing (data residency) endpoints charge a 10% uplift for GPT-5.5. Codex Fast mode is separate product metering (~1.5× speed for ~2.5× cost in OpenAI’s launch notes).

ChatGPT / Codex access (subscription)

• Free — Limited GPT-5.5 Instant (after May 2026 default rollout); not full Thinking/Pro agent access.
• Go — Roughly $8/mo (region-dependent display); more Instant volume; limited Codex; not a full frontier-agent tier.
• Plus — Roughly $20/mo USD on US list pages historically. At GPT-5.5 launch: Thinking access for Plus+; expanded Instant; practical Codex daily driver for many solos. Model picker later also shows GPT-5.6-class reasoning options—check the live matrix.
• Pro — From about $100/mo (≈5× Plus usage) to $200/mo (≈20×). Unlocks GPT-5.5 Pro-class / maximum Codex headroom; required for all-day agent volume rather than occasional runs.
• Business — About $20/user/mo annual / $25 monthly on many OpenAI pages; workspace, SSO, no training on business data by default; GPT-5.5 Instant unlimited* on Business/Enterprise comparison tables.
• Enterprise / Edu — Custom; higher admin, residency, and compliance options.

Limits & gotchas

• Price jump vs GPT-5.4 — Same work at default settings can cost more even if tokens-per-task fall. Use caching, Batch/Flex, lower effort, or GPT-5.4 / mini for routine steps.
• Not free-tier API — Platform free tier does not support gpt-5.5; you need a paid usage tier. ChatGPT Free only gets Instant-class access with tight caps.
• Subscription ≠ API credits — ChatGPT Plus/Pro do not give you unlimited production API volume. Build apps on the Platform billing path.
• Jagged capability — Claude Opus-class models still beat GPT-5.5 on some coding benches (e.g. SWE-Bench Pro public at launch: Opus 4.7 ~64.3% vs GPT-5.5 ~58.6%). HN and Reddit often split “better programmer vs better architect.”
• Agentic regressions in the wild — Some LiveBench / r/codex threads reported agentic coding regressions or “needs more guidance” versus marketing. Benchmarks ≠ your repo harness.
• Cyber safeguard friction — OpenAI warned tighter cyber classifiers may feel “annoying” for legitimate security work; use Trusted Access for Cyber or GPT-5.5-Cyber when authorized, not jailbreaks.
• UK AISI red-team note — External evaluators found a universal cyber jailbreak during testing that took ~6 hours of expert effort; OpenAI updated safeguards. Capability is High-class; public product still has monitors and enforcement.
• Personality / quirk quirks — OpenAI publicly explained a “goblins/gremlins” over-mention problem tied to a “Nerdy” personality reward; Codex system prompts and data filtering were patched. Expect occasional style bugs at the frontier.
• Hallucination & sycophancy — Independent testers still report invented facts when search is not forced, plus overconfident tone. Prefer tool-grounded workflows for citations and numbers.
• Long-context surcharge — Crossing 272K input tokens doubles input price for the session. Split work or compact context deliberately.
• No fine-tuning — gpt-5.5 does not support fine-tuning; use prompting, tools, RAG, or other models for specialty training.
• Rate limits & plan windows — API RPM/TPM by tier; ChatGPT/Codex use rolling multi-hour windows. Heavy morning Codex can empty afternoon capacity on Plus.
• Model churn — By July 2026 ChatGPT pricing already surfaces GPT-5.6 Sol/Terra/Luna lines. Product UI labels move; pin API snapshots for production.

Community sentiment

Across r/codex, r/OpenAI, r/ChatGPT, r/ChatGPTPro, and Hacker News (April–July 2026), GPT-5.5 is widely treated as a real step-up for long agent runs and coding execution, with loud debate on price, overhype, and Claude comparisons.

• Praise: Stronger persistence on multi-hour Codex tasks; fewer early stops; better conceptual debugging than GPT-5.4; competitive or better cyber evals vs restricted Anthropic Mythos Preview on UK AISI tests; token efficiency in agent loops; early access quotes from Cursor and NVIDIA engineers that went viral in the launch blog.
• Criticism: Double API price vs 5.4 with “incremental” feel for some chat users; Pro API rarely worth it; agentic coding “regression” posts on LiveBench-style leaderboards; Plus users hitting Pro-thinking or Codex caps; Instant default improvements that still feel sycophantic or invent facts when tools are off.
• Common workflows: Claude Opus for planning/architecture + GPT-5.5 for execution (HN); GPT-5.5 for coding + Claude for prose; dual $20–$200 stacks for power users who refuse single-vendor lock-in.
• Security community: Interest in GPT-5.5-Cyber / Daybreak / Patch-the-Planet style OSS vuln work, plus skepticism about public cyber capability vs gated Anthropic models.

“GPT-5.5 is the better programmer but Opus remains the better system architect.” — recurring Hacker News theme, 2026

“5.5 is about 1.5–2× more expensive overall… at lower reasoning levels, 5.4 still edges it on cost/perf.” — HN cost-analysis thread on OpenRouter figures

Who should use it

• Software engineers running agentic coding in Codex, Cursor, or custom harnesses who need multi-file, multi-hour persistence and strong tool loops.
• Product, research, and ops teams doing messy knowledge work: research synthesis, spreadsheet modeling, multi-tool computer use, long document pipelines.
• API builders who need frontier quality with pinable snapshots, structured outputs, and MCP/tool ecosystems—and can afford $5/$30 rates or route intelligently.
• Security teams with authorized access evaluating TAC or GPT-5.5-Cyber for defensive workflows (code review, vuln triage, malware analysis)—not casual “try hacking” use.
• Not ideal as a default for: high-volume cheap chat, pure creative writing where Claude taste wins, or production automation that must stay under tight token budgets without a router.

Alternatives

• ChatGPT — Full product surface (chat, images, voice, GPTs, plan billing). Use when you care about the app, not a single model ID.
• OpenAI Codex — Coding agent harness where GPT-5.5 often shines; compare limits vs raw API.
• OpenAI — Platform overview: API, models, enterprise, and adjacent products.
• Claude / Claude Code — Strong rival for architecture, prose, and Anthropic’s agent coding stack; often paired with GPT-5.5 rather than replaced by it.
• Gemini — Google’s frontier alternative, especially inside Workspace and Google Cloud stacks.
• Cursor — IDE that routes multiple models (including OpenAI) for day-to-day coding.
• GitHub Copilot — Editor-native assistant with multi-model backends; different metering and GitHub integration.
• Grok — xAI alternative for users who want a different frontier stack or X integration.
• GPT4All — Local/open weights path when cloud frontier pricing or data residency rules out GPT-5.5.

Verdict

GPT-5.5 is a serious agentic frontier model, not a cosmetic version bump. Official and third-party evidence supports real gains on terminal/agent coding, computer use, and long-horizon knowledge work, with competitive cyber capability that forced a heavier safeguard stack. The trade-offs are equally real: roughly 2× token price vs GPT-5.4, mixed public SWE benches versus Claude, subscription caps that push power users to Pro, and residual hallucination/tone issues when tools are not in the loop.

Bottom line: Choose GPT-5.5 when the task is “finish this multi-step job with tools,” especially in Codex or a careful API agent. Stay on GPT-5.4 / mini or a competitor for volume and cost. Use GPT-5.5 Pro sparingly. Re-check the live model picker—by mid-2026 OpenAI already ships later GPT-5.6-branded options in ChatGPT while API gpt-5.5 remains a first-class, priced model ID.