Technology

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.

4
GPT-5.5
vs
2
GPT-5.3-Codex
Quick Verdict

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-CodexWinner
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 Score4/ 82/ 82 ties
Sunset Status
GPT-5.5
Current default model, actively updated
GPT-5.3-Codex
Frozen LTS snapshot, guaranteed through Feb 4, 2027
Overall Benchmark
GPT-5.5
73.51/100 on BenchLM, public rank #9
GPT-5.3-Codex
66.69/100 on BenchLM, public rank #26
Coding Specific
GPT-5.5
Broader general/agentic reasoning strength
GPT-5.3-Codex
Wins BenchLM's coding category; devs report better codebase handling
Pricing
GPT-5.5
$5/M input, $30/M output
GPT-5.3-Codex
$1.75/M input, $14/M output -- about 1/3 the cost
Context Window
GPT-5.5
~1M tokens (922K in / 128K out)
GPT-5.3-Codex
400K tokens
Availability
GPT-5.5
Default across ChatGPT/Codex UI for Plus/Pro/Business/Enterprise
GPT-5.3-Codex
API + Copilot Business/Enterprise only; pulled from ChatGPT subscription Codex UI June 2, 2026
Stability
GPT-5.5
Actively iterated, no fixed retirement date announced
GPT-5.3-Codex
Frozen feature set (LTS) -- predictable for compliance review cycles
Hallucination Rate
GPT-5.5
~60% fewer hallucinations vs prior generation (OpenAI-reported)
GPT-5.3-Codex
Not benchmarked on the same suite

Key Statistics

Real data from verified industry sources to support your decision.

73.51 vs 66.69 out of 100 overall

BenchLM.ai

$5.00/$30.00 vs $1.75/$14.00 per million tokens (in/out)

llm-stats.com

~1M (922K in / 128K out) vs 400K token context window

WaveSpeedAI

5 Codex snapshots retire July 23, 2026: gpt-5-codex, gpt-5.1-codex, gpt-5.1-codex-max, gpt-5.2-codex, gpt-5.1-codex-mini

Developers Digest (OpenAI deprecations page)

GPT-5.3-Codex LTS guaranteed through February 4, 2027; Copilot Business/Enterprise base model since May 17, 2026

GitHub Changelog

GPT-5.5 released April 23, 2026 as OpenAI's first fully retrained agentic model

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.

Five Codex-branded snapshots -- gpt-5-codex, gpt-5.1-codex, gpt-5.1-codex-max, gpt-5.2-codex, and gpt-5.1-codex-mini -- plus the GPT-5/5.1 chat-latest aliases and both deep-research models. GPT-5.3-Codex is not on the list.
No. It's GitHub's first Long-Term-Support model, guaranteed available through February 4, 2027, and has been the default base model for Copilot Business and Enterprise since May 17, 2026. It was pulled from the ChatGPT subscription Codex UI on June 2, 2026, but stays available via the API and Copilot.
It wins BenchLM's coding-specific benchmark category and costs roughly a third as much per token. Threads on OpenAI's own developer forum describe GPT-5.5 as over-editing and burning tokens on codebase tasks GPT-5.3-Codex handles more cleanly -- a consistent workflow complaint, though not an independently verified benchmark.
OpenAI's own mapping sends every retiring July-23 Codex snapshot to gpt-5.5 -- that's the safe default. If cost or coding-specific accuracy matters more than overall benchmark rank, gpt-5.3-codex is a deliberate alternative, not just a stopgap.

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