GPT-5.5 vs GPT-5.3-Codex: Which to Use After the Codex Sunset (2026)
GPT-5.5 vs GPT-5.3-Codex after OpenAI's July 23, 2026 Codex sunset: what's actually retiring, pricing, benchmarks, and which model to migrate to.
GPT-5.5 wins on paper: a 73.51-vs-66.69 BenchLM overall score, a roughly 2.5x larger context window, and OpenAI's own migration table sends every retiring July-23 Codex snapshot to it by default. If you're just patching a broken config reference, gpt-5.5 is the safe, supported answer. But 'safe default' isn't the same as 'best for coding.' GPT-5.3-Codex wins BenchLM's coding-specific category, costs about a third as much per token ($1.75/$14 per million vs $5/$30), and is the model GitHub itself chose as the frozen, compliance-friendly base for Copilot Business and Enterprise -- a deliberate bet on predictable behavior over frontier benchmark rank. Developer forum threads on OpenAI's own community site (not an independently verified benchmark, but a consistent pattern across multiple posters) describe GPT-5.5 as over-editing and burning tokens on codebase tasks that GPT-5.3-Codex handles more surgically. The honest read: if your July-23 deadline is about a dying snapshot reference, migrate to gpt-5.5 and move on. If you're choosing a coding model on its own merits, gpt-5.3-codex's LTS guarantee through February 2027, lower cost, and coding-category benchmark win make it the deliberate choice, not a legacy holdover.
Detailed Comparison
A side-by-side analysis of key factors to help you make the right choice.
| Factor | GPT-5.5Recommended | GPT-5.3-Codex | Winner |
|---|---|---|---|
| Sunset Status | Current default model, actively updated | Frozen LTS snapshot, guaranteed through Feb 4, 2027 | |
| Overall Benchmark | 73.51/100 on BenchLM, public rank #9 | 66.69/100 on BenchLM, public rank #26 | |
| Coding Specific | Broader general/agentic reasoning strength | Wins BenchLM's coding category; devs report better codebase handling | |
| Pricing | $5/M input, $30/M output | $1.75/M input, $14/M output -- about 1/3 the cost | |
| Context Window | ~1M tokens (922K in / 128K out) | 400K tokens | |
| Availability | Default across ChatGPT/Codex UI for Plus/Pro/Business/Enterprise | API + Copilot Business/Enterprise only; pulled from ChatGPT subscription Codex UI June 2, 2026 | |
| Stability | Actively iterated, no fixed retirement date announced | Frozen feature set (LTS) -- predictable for compliance review cycles | |
| Hallucination Rate | ~60% fewer hallucinations vs prior generation (OpenAI-reported) | Not benchmarked on the same suite | |
| Total Score | 4/ 8 | 2/ 8 | 2 ties |
Key Statistics
Real data from verified industry sources to support your decision.
Developers Digest (OpenAI deprecations page)
GitHub Changelog
WaveSpeedAI
All statistics come from verified third-party sources. Source, year, and direct link are shown on each metric.
When to Choose Each Option
Clear guidance based on your specific situation and needs.
Choose GPT-5.5 when...
- You want OpenAI's actively updated, highest-overall-benchmarked model
- Your workload needs the ~1M-token context window
- You're on a ChatGPT Plus/Pro plan without Copilot Business/Enterprise access
- Your code references a snapshot retiring July 23, 2026, and you want OpenAI's official migration path
Choose GPT-5.3-Codex when...
- You run GitHub Copilot Business or Enterprise and want a frozen, compliance-friendly base model
- Token cost matters and coding is the primary workload
- You've found GPT-5.5 over-edits or wastes tokens on your codebase
- You need model behavior to stay fixed through February 2027 for security/audit review cycles
Our Recommendation
GPT-5.5 wins on paper: a 73.51-vs-66.69 BenchLM overall score, a roughly 2.5x larger context window, and OpenAI's own migration table sends every retiring July-23 Codex snapshot to it by default. If you're just patching a broken config reference, gpt-5.5 is the safe, supported answer. But 'safe default' isn't the same as 'best for coding.' GPT-5.3-Codex wins BenchLM's coding-specific category, costs about a third as much per token ($1.75/$14 per million vs $5/$30), and is the model GitHub itself chose as the frozen, compliance-friendly base for Copilot Business and Enterprise -- a deliberate bet on predictable behavior over frontier benchmark rank. Developer forum threads on OpenAI's own community site (not an independently verified benchmark, but a consistent pattern across multiple posters) describe GPT-5.5 as over-editing and burning tokens on codebase tasks that GPT-5.3-Codex handles more surgically. The honest read: if your July-23 deadline is about a dying snapshot reference, migrate to gpt-5.5 and move on. If you're choosing a coding model on its own merits, gpt-5.3-codex's LTS guarantee through February 2027, lower cost, and coding-category benchmark win make it the deliberate choice, not a legacy holdover.
Frequently Asked Questions
Common questions about this comparison answered.
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