Both are OpenAI models. GPT-6 Luna is the newer, generally stronger default; reach for GPT-5.3-Codex when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.3-Codex and GPT-6 Luna are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. GPT-6 Luna is openAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. 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-6 Luna is about 18× cheaper on input ($0.1/$0.5 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-6 Luna holds 2.6× more — 1.05M tokens (~1,575 pages) vs 400K (~600 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-6 Luna is the newer model by about 8 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.3-Codex
GPT-6 Luna
Provider
OpenAI (US)
OpenAI (US)
Released
February 5, 2026
September 22, 2026
Context window
400K (~600 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$1.75/$14 per 1M tokens
$0.1/$0.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, code
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Dedicated coding agent: GPT-5.3-Codex — GPT-5.3-Codex lists dedicated coding agent among its strengths; GPT-6 Luna does not.
CLI and IDE integration: GPT-5.3-Codex — GPT-5.3-Codex lists cLI and IDE integration among its strengths; GPT-6 Luna does not.
Autonomous software tasks: GPT-5.3-Codex — GPT-5.3-Codex lists autonomous software tasks among its strengths; GPT-6 Luna does not.
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume: GPT-6 Luna — At $0.1/$0.5 per 1M tokens it undercuts GPT-5.3-Codex ($1.75/$14 per 1M tokens), and that gap compounds at volume.
Available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers: GPT-6 Luna — OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it runs cheaper at $0.1/$0.5 per 1M tokens.
Cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family: GPT-6 Luna — OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it carries the larger 1.05M tokens context.
Lowest cost at scale: GPT-6 Luna — At $0.1/$0.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-6 Luna — Its 1.05M tokens window is about 2.6× larger than GPT-5.3-Codex's 400K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-6 Luna — At $0.1/$0.5 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-6 Luna — Larger 1.05M tokens window fits more in one prompt.
Anyone whose priority is dedicated coding agent: GPT-5.3-Codex — It is specifically built for that.
Anyone whose priority is openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume: GPT-6 Luna — That is its strongest area.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 5, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs are real: 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.
GPT-6 Luna: where it fits
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. Released September 22, 2026 by OpenAI, it is built for openAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers, cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family, and 1.05M-token context window carried down from the flagship tier.
Its trade-offs: less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems, and as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh. At $0.1 in / $0.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because GPT-5.3-Codex and GPT-6 Luna come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-6 Luna 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-6 Luna and drop down only with a concrete reason.
Frequently asked questions
Is GPT-5.3-Codex or GPT-6 Luna 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-5.3-Codex leans toward dedicated coding agent while GPT-6 Luna leans toward openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.3-Codex or GPT-6 Luna?
GPT-6 Luna is cheaper — $1.75/$14 per 1M tokens vs $0.1/$0.5 per 1M tokens, roughly 18× apart on input.
Which has the bigger context window?
GPT-6 Luna — 1.05M tokens vs 400K, about 2.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GPT-5.3-Codex to GPT-6 Luna?
Since both are OpenAI models, the newer one (GPT-6 Luna) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-5.3-Codex or GPT-6 Luna?
GPT-6 Luna — released September 22, 2026, about 8 months after GPT-5.3-Codex.
GPT-5.3-Codex vs GPT-6 Luna
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-6 Luna is the newer, generally stronger default; reach for GPT-5.3-Codex when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.3-Codex and GPT-6 Luna are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. GPT-6 Luna is openAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. 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-6 Luna is about 18× cheaper on input ($0.1/$0.5 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-6 Luna holds 2.6× more — 1.05M tokens (~1,575 pages) vs 400K (~600 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-6 Luna is the newer model by about 8 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.3-Codex
GPT-6 Luna
Provider
OpenAI (US)
OpenAI (US)
Released
February 5, 2026
September 22, 2026
Context window
400K (~600 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$1.75/$14 per 1M tokens
$0.1/$0.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, code
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Dedicated coding agent
GPT-5.3-Codex
GPT-5.3-Codex lists dedicated coding agent among its strengths; GPT-6 Luna does not.
CLI and IDE integration
GPT-5.3-Codex
GPT-5.3-Codex lists cLI and IDE integration among its strengths; GPT-6 Luna does not.
Autonomous software tasks
GPT-5.3-Codex
GPT-5.3-Codex lists autonomous software tasks among its strengths; GPT-6 Luna does not.
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume
GPT-6 Luna
At $0.1/$0.5 per 1M tokens it undercuts GPT-5.3-Codex ($1.75/$14 per 1M tokens), and that gap compounds at volume.
Available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers
GPT-6 Luna
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it runs cheaper at $0.1/$0.5 per 1M tokens.
Cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family
GPT-6 Luna
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth — and it carries the larger 1.05M tokens context.
Lowest cost at scale
GPT-6 Luna
At $0.1/$0.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-6 Luna
Its 1.05M tokens window is about 2.6× larger than GPT-5.3-Codex's 400K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-6 Luna
At $0.1/$0.5 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-6 Luna
Larger 1.05M tokens window fits more in one prompt.
Anyone whose priority is dedicated coding agent
→ GPT-5.3-Codex
It is specifically built for that.
Anyone whose priority is openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume
→ GPT-6 Luna
That is its strongest area.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 5, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs are real: 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.
GPT-6 Luna: where it fits
OpenAI's cheapest GPT-6 tier, released September 22, 2026 alongside GPT-6 Sol — $0.10/$0.50 per million tokens, built for speed over depth. Released September 22, 2026 by OpenAI, it is built for openAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, available to Free and Go plan users in the ChatGPT desktop app, not gated to paid tiers, cache reads at $0.01/MTok — a 90% discount, the cheapest in the GPT-6 family, and 1.05M-token context window carried down from the flagship tier.
Its trade-offs: less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems, and as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh. At $0.1 in / $0.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because GPT-5.3-Codex and GPT-6 Luna come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-6 Luna 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-6 Luna and drop down only with a concrete reason.
Want both GPT-5.3-Codex and GPT-6 Luna 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.
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-5.3-Codex leans toward dedicated coding agent while GPT-6 Luna leans toward openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.3-Codex or GPT-6 Luna?
GPT-6 Luna is cheaper — $1.75/$14 per 1M tokens vs $0.1/$0.5 per 1M tokens, roughly 18× apart on input.
Which has the bigger context window?
GPT-6 Luna — 1.05M tokens vs 400K, about 2.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GPT-5.3-Codex to GPT-6 Luna?
Since both are OpenAI models, the newer one (GPT-6 Luna) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-5.3-Codex or GPT-6 Luna?
GPT-6 Luna — released September 22, 2026, about 8 months after GPT-5.3-Codex.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.