Both are OpenAI models. GPT-5.6 Luna is the newer, generally stronger default; reach for GPT-5.4 when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.4 and GPT-5.6 Luna are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-5.4 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. 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. 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-5.6 Luna is about 2.5× cheaper on input ($1/$6 per 1M tokens vs $2.5/$15 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: GPT-5.6 Luna is the newer model by about 4 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.4
GPT-5.6 Luna
Provider
OpenAI (US)
OpenAI (US)
Released
March 5, 2026
July 9, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$15 per 1M tokens
$1/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong general-purpose default: GPT-5.4 — A core design strength of GPT-5.4.
Coding and software engineering: GPT-5.4 — A core design strength of GPT-5.4.
Document understanding and tool use: GPT-5.4 — A core design strength of GPT-5.4.
Cheapest GPT-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Lowest cost at scale: GPT-5.6 Luna — At $1/$6 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-5.6 Luna — At $1/$6 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is strong general-purpose default: GPT-5.4 — It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — That is its strongest area.
GPT-5.4: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs are real: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 out per million tokens, it sits in the mid price band.
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: 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.
The bottom line for this matchup
Because GPT-5.4 and GPT-5.6 Luna come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-5.6 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-5.6 Luna and drop down only with a concrete reason.
Frequently asked questions
Is GPT-5.4 or GPT-5.6 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-5.4 leans toward strong general-purpose default while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 or GPT-5.6 Luna?
GPT-5.6 Luna is cheaper — $2.5/$15 per 1M tokens vs $1/$6 per 1M tokens, roughly 2.5× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GPT-5.4 to GPT-5.6 Luna?
Since both are OpenAI models, the newer one (GPT-5.6 Luna) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-5.4 or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 4 months after GPT-5.4.
GPT-5.4 vs GPT-5.6 Luna
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-5.6 Luna is the newer, generally stronger default; reach for GPT-5.4 when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.4 and GPT-5.6 Luna are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-5.4 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. 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. 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-5.6 Luna is about 2.5× cheaper on input ($1/$6 per 1M tokens vs $2.5/$15 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-5.6 Luna is the newer model by about 4 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.4
GPT-5.6 Luna
Provider
OpenAI (US)
OpenAI (US)
Released
March 5, 2026
July 9, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$15 per 1M tokens
$1/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong general-purpose default
GPT-5.4
A core design strength of GPT-5.4.
Coding and software engineering
GPT-5.4
A core design strength of GPT-5.4.
Document understanding and tool use
GPT-5.4
A core design strength of GPT-5.4.
Cheapest GPT-5.6 tier for high-volume drafting and automation
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Lowest cost at scale
GPT-5.6 Luna
At $1/$6 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-5.6 Luna
At $1/$6 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is strong general-purpose default
→ GPT-5.4
It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation
→ GPT-5.6 Luna
That is its strongest area.
GPT-5.4: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs are real: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 out per million tokens, it sits in the mid price band.
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: 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.
The bottom line for this matchup
Because GPT-5.4 and GPT-5.6 Luna come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-5.6 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-5.6 Luna and drop down only with a concrete reason.
Want both GPT-5.4 and GPT-5.6 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-5.4 leans toward strong general-purpose default while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 or GPT-5.6 Luna?
GPT-5.6 Luna is cheaper — $2.5/$15 per 1M tokens vs $1/$6 per 1M tokens, roughly 2.5× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GPT-5.4 to GPT-5.6 Luna?
Since both are OpenAI models, the newer one (GPT-5.6 Luna) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-5.4 or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 4 months after GPT-5.4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.