Both are OpenAI models. GPT-6 Luna is the newer, generally stronger default; reach for GPT-5.6 Luna when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.6 Luna 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-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. 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 10× cheaper on input ($0.1/$0.5 per 1M tokens vs $1/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: 1M vs 1.05M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: GPT-6 Luna is the newer model by about 3 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.6 Luna
GPT-6 Luna
Provider
OpenAI (US)
OpenAI (US)
Released
July 9, 2026
September 22, 2026
Context window
1M (~1,500 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$1/$6 per 1M tokens
$0.1/$0.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Fast, affordable execution while keeping respectable coding: GPT-5.6 Luna — GPT-5.6 Luna lists fast, affordable execution while keeping respectable coding among its strengths; GPT-6 Luna does not.
Same 1M context and programmatic tool calling as its siblings: GPT-5.6 Luna — GPT-5.6 Luna lists same 1M context and programmatic tool calling as its siblings 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-5.6 Luna ($1/$6 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 — GPT-5.6 Luna is comparatively weak here — lowest raw capability of the three GPT-5.6 tiers; no open weights
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 runs cheaper at $0.1/$0.5 per 1M tokens.
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.
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-5.6 Luna, 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 cheapest gpt-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — 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-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs are real: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 out per million tokens, it sits in the budget 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-5.6 Luna 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-5.6 Luna 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-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation 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-5.6 Luna or GPT-6 Luna?
GPT-6 Luna is cheaper — $1/$6 per 1M tokens vs $0.1/$0.5 per 1M tokens, roughly 10× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1.05M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GPT-5.6 Luna 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-5.6 Luna or GPT-6 Luna?
GPT-6 Luna — released September 22, 2026, about 3 months after GPT-5.6 Luna.
GPT-5.6 Luna 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-5.6 Luna when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.6 Luna 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-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. 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 10× cheaper on input ($0.1/$0.5 per 1M tokens vs $1/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: 1M vs 1.05M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-6 Luna is the newer model by about 3 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.6 Luna
GPT-6 Luna
Provider
OpenAI (US)
OpenAI (US)
Released
July 9, 2026
September 22, 2026
Context window
1M (~1,500 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$1/$6 per 1M tokens
$0.1/$0.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.6 tier for high-volume drafting and automation
GPT-5.6 Luna
GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Fast, affordable execution while keeping respectable coding
GPT-5.6 Luna
GPT-5.6 Luna lists fast, affordable execution while keeping respectable coding among its strengths; GPT-6 Luna does not.
Same 1M context and programmatic tool calling as its siblings
GPT-5.6 Luna
GPT-5.6 Luna lists same 1M context and programmatic tool calling as its siblings 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-5.6 Luna ($1/$6 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
GPT-5.6 Luna is comparatively weak here — lowest raw capability of the three GPT-5.6 tiers; no open weights
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 runs cheaper at $0.1/$0.5 per 1M tokens.
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.
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-5.6 Luna, 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 cheapest gpt-5.6 tier for high-volume drafting and automation
→ GPT-5.6 Luna
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-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs are real: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 out per million tokens, it sits in the budget 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-5.6 Luna 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-5.6 Luna 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-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation 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-5.6 Luna or GPT-6 Luna?
GPT-6 Luna is cheaper — $1/$6 per 1M tokens vs $0.1/$0.5 per 1M tokens, roughly 10× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1.05M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GPT-5.6 Luna 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-5.6 Luna or GPT-6 Luna?
GPT-6 Luna — released September 22, 2026, about 3 months after GPT-5.6 Luna.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.