Both are OpenAI models. GPT-6 Sol is the newer, generally stronger default; reach for GPT-5.6 Luna when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-5.6 Luna and GPT-6 Sol 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 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. 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× cheaper on input ($1/$6 per 1M tokens vs $2/$10 per 1M tokens) — meaningful once you are processing millions of tokens a month.
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 Sol 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 Sol
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
$2/$10 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 — At $1/$6 per 1M tokens it undercuts GPT-6 Sol ($2/$10 per 1M tokens), and that gap compounds at volume.
Fast, affordable execution while keeping respectable coding: GPT-5.6 Luna — The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning — and it runs cheaper at $1/$6 per 1M tokens.
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 Sol does not.
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — GPT-5.6 Luna is comparatively weak here — weak long-context recall deep in its 1M window (MRCR far below Sol)
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol: GPT-6 Sol — OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30): GPT-6 Sol — GPT-6 Sol lists priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30) among its strengths; GPT-5.6 Luna does not.
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-6 Sol, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Sol — 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 everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — 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 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Because GPT-5.6 Luna and GPT-6 Sol come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-6 Sol 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 Sol and drop down only with a concrete reason.
Frequently asked questions
Is GPT-5.6 Luna or GPT-6 Sol 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 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.6 Luna or GPT-6 Sol?
GPT-5.6 Luna is cheaper — $1/$6 per 1M tokens vs $2/$10 per 1M tokens, roughly 2× 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 Sol?
Since both are OpenAI models, the newer one (GPT-6 Sol) 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 Sol?
GPT-6 Sol — released September 22, 2026, about 3 months after GPT-5.6 Luna.
GPT-5.6 Luna vs GPT-6 Sol
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-6 Sol is the newer, generally stronger default; reach for GPT-5.6 Luna when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-5.6 Luna and GPT-6 Sol 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 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. 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× cheaper on input ($1/$6 per 1M tokens vs $2/$10 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸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 Sol 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 Sol
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
$2/$10 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
At $1/$6 per 1M tokens it undercuts GPT-6 Sol ($2/$10 per 1M tokens), and that gap compounds at volume.
Fast, affordable execution while keeping respectable coding
GPT-5.6 Luna
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning — and it runs cheaper at $1/$6 per 1M tokens.
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 Sol does not.
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment
GPT-6 Sol
GPT-5.6 Luna is comparatively weak here — weak long-context recall deep in its 1M window (MRCR far below Sol)
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol
GPT-6 Sol
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30)
GPT-6 Sol
GPT-6 Sol lists priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30) among its strengths; GPT-5.6 Luna does not.
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-6 Sol, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Sol
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 everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment
→ GPT-6 Sol
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 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Because GPT-5.6 Luna and GPT-6 Sol come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-6 Sol 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 Sol and drop down only with a concrete reason.
Want both GPT-5.6 Luna and GPT-6 Sol 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 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.6 Luna or GPT-6 Sol?
GPT-5.6 Luna is cheaper — $1/$6 per 1M tokens vs $2/$10 per 1M tokens, roughly 2× 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 Sol?
Since both are OpenAI models, the newer one (GPT-6 Sol) 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 Sol?
GPT-6 Sol — 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.