Both are OpenAI models. GPT-6 Luna is the newer, generally stronger default; reach for gpt-oss-120b when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-6 Luna and gpt-oss-120b are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. 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. gpt-oss-120b is openAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Cost model: gpt-oss-120b ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-6 Luna is API-metered at $0.1/$0.5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: GPT-6 Luna holds 8× more — 1.05M tokens (~1,575 pages) vs 131K (~197 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 14 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-6 Luna
gpt-oss-120b
Provider
OpenAI (US)
OpenAI (US)
Released
September 22, 2026
August 5, 2025
Context window
1.05M tokens (~1,575 pages)
131K (~197 pages)
Price (in/out)
$0.1/$0.5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume: GPT-6 Luna — Its 1.05M tokens window holds about 8× more than gpt-oss-120b's 131K in a single prompt.
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 carries the larger 1.05M tokens context.
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 is the newer of the two.
Self-hostable on a single 80GB H100 GPU via MXFP4: gpt-oss-120b — Open weights make this possible at all — GPT-6 Luna is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high): gpt-oss-120b — GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Agentic tool use, function calling, and code execution: gpt-oss-120b — OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and its weights are open while GPT-6 Luna is API-only.
Lowest cost at scale: gpt-oss-120b — Its weights are open, so at volume you pay for your own hardware instead of GPT-6 Luna's $0.1/$0.5 per 1M tokens.
Largest single-prompt input: GPT-6 Luna — Its 1.05M tokens window is about 8× larger than gpt-oss-120b's 131K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: gpt-oss-120b — At Open weight (self-host / free) it undercuts GPT-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.
A team with data-privacy or self-hosting needs: gpt-oss-120b — Open weights let you run it on your own hardware; GPT-6 Luna is API-only.
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 — It is specifically built for that.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4: gpt-oss-120b — That is its strongest area.
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 are real: 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.
gpt-oss-120b: where it fits
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Released August 5, 2025 by OpenAI, it is built for self-hostable on a single 80GB H100 GPU via MXFP4, configurable reasoning depth (low/medium/high), agentic tool use, function calling, and code execution, and full chain-of-thought visibility for debugging.
Its trade-offs: text-only, no image, audio, or video input, and 131K context and 5.1B active params trail the largest frontier closed models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Because GPT-6 Luna and gpt-oss-120b 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-6 Luna or gpt-oss-120b better for coding?
Public SWE-Bench figures are not available for GPT-6 Luna, so the honest test is your own repository — run an identical real bug through both. By design, 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 while gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Luna or gpt-oss-120b?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6 Luna is API-metered at $0.1/$0.5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
GPT-6 Luna — 1.05M tokens vs 131K, about 8× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from gpt-oss-120b 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-6 Luna or gpt-oss-120b?
GPT-6 Luna — released September 22, 2026, about 14 months after gpt-oss-120b.
GPT-6 Luna vs gpt-oss-120b
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-oss-120b when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-6 Luna and gpt-oss-120b are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. 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. gpt-oss-120b is openAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. 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
▸Cost model: gpt-oss-120b ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-6 Luna is API-metered at $0.1/$0.5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: GPT-6 Luna holds 8× more — 1.05M tokens (~1,575 pages) vs 131K (~197 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 14 months (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-6 Luna
gpt-oss-120b
Provider
OpenAI (US)
OpenAI (US)
Released
September 22, 2026
August 5, 2025
Context window
1.05M tokens (~1,575 pages)
131K (~197 pages)
Price (in/out)
$0.1/$0.5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
OpenAI's cheapest GPT-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume
GPT-6 Luna
Its 1.05M tokens window holds about 8× more than gpt-oss-120b's 131K in a single prompt.
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 carries the larger 1.05M tokens context.
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 is the newer of the two.
Self-hostable on a single 80GB H100 GPU via MXFP4
gpt-oss-120b
Open weights make this possible at all — GPT-6 Luna is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Agentic tool use, function calling, and code execution
gpt-oss-120b
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and its weights are open while GPT-6 Luna is API-only.
Lowest cost at scale
gpt-oss-120b
Its weights are open, so at volume you pay for your own hardware instead of GPT-6 Luna's $0.1/$0.5 per 1M tokens.
Largest single-prompt input
GPT-6 Luna
Its 1.05M tokens window is about 8× larger than gpt-oss-120b's 131K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ gpt-oss-120b
At Open weight (self-host / free) it undercuts GPT-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.
A team with data-privacy or self-hosting needs
→ gpt-oss-120b
Open weights let you run it on your own hardware; GPT-6 Luna is API-only.
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
It is specifically built for that.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4
→ gpt-oss-120b
That is its strongest area.
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 are real: 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.
gpt-oss-120b: where it fits
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Released August 5, 2025 by OpenAI, it is built for self-hostable on a single 80GB H100 GPU via MXFP4, configurable reasoning depth (low/medium/high), agentic tool use, function calling, and code execution, and full chain-of-thought visibility for debugging.
Its trade-offs: text-only, no image, audio, or video input, and 131K context and 5.1B active params trail the largest frontier closed models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Because GPT-6 Luna and gpt-oss-120b 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-6 Luna and gpt-oss-120b 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 GPT-6 Luna, so the honest test is your own repository — run an identical real bug through both. By design, 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 while gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Luna or gpt-oss-120b?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6 Luna is API-metered at $0.1/$0.5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
GPT-6 Luna — 1.05M tokens vs 131K, about 8× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from gpt-oss-120b 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-6 Luna or gpt-oss-120b?
GPT-6 Luna — released September 22, 2026, about 14 months after gpt-oss-120b.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.