Both are OpenAI models. GPT-5.3-Codex is the newer, generally stronger default; reach for GPT-4o mini when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-4o mini and GPT-5.3-Codex are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-4o mini is openAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Price: GPT-4o mini is about 12× cheaper on input ($0.15/$0.6 per 1M tokens vs $1.75/$14 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: GPT-5.3-Codex holds 3.1× more — 400K (~600 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: GPT-5.3-Codex is the newer model by about 20 months (released February 24, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-4o mini
GPT-5.3-Codex
Provider
OpenAI (US)
OpenAI (US)
Released
July 18, 2024
February 24, 2026
Context window
128K (~192 pages)
400K (~600 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$1.75/$14 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very low cost per token for its capability tier: GPT-4o mini — A core design strength of GPT-4o mini.
Strong coding for a small model (87.2% HumanEval): GPT-4o mini — A core design strength of GPT-4o mini.
Leading MMLU among peer small models (82%): GPT-4o mini — A core design strength of GPT-4o mini.
Dedicated coding agent: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
CLI and IDE integration: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Autonomous software tasks: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Lowest cost at scale: GPT-4o mini — At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-5.3-Codex — Its 400K window is about 3.1× larger, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-4o mini — At $0.15/$0.6 per 1M tokens it undercuts GPT-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.3-Codex — Larger 400K window fits more in one prompt.
Anyone whose priority is very low cost per token for its capability tier: GPT-4o mini — It is specifically built for that.
Anyone whose priority is dedicated coding agent: GPT-5.3-Codex — That is its strongest area.
GPT-4o mini: where it fits
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Released July 18, 2024 by OpenAI, it is built for very low cost per token for its capability tier, strong coding for a small model (87.2% HumanEval), leading MMLU among peer small models (82%), and text and image (vision) understanding in the API.
Its trade-offs are real: only 128K context with an October 2023 knowledge cutoff, and weaker on hard reasoning and coding than frontier models. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Because GPT-4o mini and GPT-5.3-Codex come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-5.3-Codex is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GPT-5.3-Codex and drop down only with a concrete reason.
Frequently asked questions
Is GPT-4o mini or GPT-5.3-Codex better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4o mini leans toward very low cost per token for its capability tier while GPT-5.3-Codex leans toward dedicated coding agent, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or GPT-5.3-Codex?
GPT-4o mini is cheaper — $0.15/$0.6 per 1M tokens vs $1.75/$14 per 1M tokens, roughly 12× apart on input.
Which has the bigger context window?
GPT-5.3-Codex — 400K vs 128K, about 3.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GPT-4o mini to GPT-5.3-Codex?
Since both are OpenAI models, the newer one (GPT-5.3-Codex) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-4o mini or GPT-5.3-Codex?
GPT-5.3-Codex — released February 24, 2026, about 20 months after GPT-4o mini.
GPT-4o mini vs GPT-5.3-Codex
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-5.3-Codex is the newer, generally stronger default; reach for GPT-4o mini when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-4o mini and GPT-5.3-Codex are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-4o mini is openAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Price: GPT-4o mini is about 12× cheaper on input ($0.15/$0.6 per 1M tokens vs $1.75/$14 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: GPT-5.3-Codex holds 3.1× more — 400K (~600 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: GPT-5.3-Codex is the newer model by about 20 months (released February 24, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-4o mini
GPT-5.3-Codex
Provider
OpenAI (US)
OpenAI (US)
Released
July 18, 2024
February 24, 2026
Context window
128K (~192 pages)
400K (~600 pages)
Price (in/out)
$0.15/$0.6 per 1M tokens
$1.75/$14 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very low cost per token for its capability tier
GPT-4o mini
A core design strength of GPT-4o mini.
Strong coding for a small model (87.2% HumanEval)
GPT-4o mini
A core design strength of GPT-4o mini.
Leading MMLU among peer small models (82%)
GPT-4o mini
A core design strength of GPT-4o mini.
Dedicated coding agent
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
CLI and IDE integration
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Autonomous software tasks
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Lowest cost at scale
GPT-4o mini
At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-5.3-Codex
Its 400K window is about 3.1× larger, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts GPT-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.3-Codex
Larger 400K window fits more in one prompt.
Anyone whose priority is very low cost per token for its capability tier
→ GPT-4o mini
It is specifically built for that.
Anyone whose priority is dedicated coding agent
→ GPT-5.3-Codex
That is its strongest area.
GPT-4o mini: where it fits
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Released July 18, 2024 by OpenAI, it is built for very low cost per token for its capability tier, strong coding for a small model (87.2% HumanEval), leading MMLU among peer small models (82%), and text and image (vision) understanding in the API.
Its trade-offs are real: only 128K context with an October 2023 knowledge cutoff, and weaker on hard reasoning and coding than frontier models. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Because GPT-4o mini and GPT-5.3-Codex come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-5.3-Codex is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GPT-5.3-Codex and drop down only with a concrete reason.
Want both GPT-4o mini and GPT-5.3-Codex without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is GPT-4o mini or GPT-5.3-Codex better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4o mini leans toward very low cost per token for its capability tier while GPT-5.3-Codex leans toward dedicated coding agent, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4o mini or GPT-5.3-Codex?
GPT-4o mini is cheaper — $0.15/$0.6 per 1M tokens vs $1.75/$14 per 1M tokens, roughly 12× apart on input.
Which has the bigger context window?
GPT-5.3-Codex — 400K vs 128K, about 3.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GPT-4o mini to GPT-5.3-Codex?
Since both are OpenAI models, the newer one (GPT-5.3-Codex) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-4o mini or GPT-5.3-Codex?
GPT-5.3-Codex — released February 24, 2026, about 20 months after GPT-4o mini.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.