Pick GPT-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume or available to free and go plan users in the chatgpt desktop app, not gated to paid tiers. Pick MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%) or microsoft's first in-house flagship reasoner, trained without openai distillation. On a tight budget at scale, MAI-Thinking-1 is the value pick.
GPT-6 Luna (OpenAI) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. 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. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: GPT-6 Luna holds 4.1× more — 1.05M tokens (~1,575 pages) vs 256K (~384 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 41 days (released September 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-6 Luna
MAI-Thinking-1
Provider
OpenAI (US)
Microsoft (US)
Released
September 22, 2026
August 12, 2026
Context window
1.05M tokens (~1,575 pages)
256K (~384 pages)
Price (in/out)
$0.1/$0.5 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
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 4.1× more than MAI-Thinking-1's 256K 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.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation: MAI-Thinking-1 — GPT-6 Luna is comparatively weak here — as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh
Efficient reasoning at low token cost for its class: MAI-Thinking-1 — MAI-Thinking-1 lists efficient reasoning at low token cost for its class among its strengths; GPT-6 Luna does not.
Lowest cost at scale: MAI-Thinking-1 — 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 4.1× larger than MAI-Thinking-1's 256K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MAI-Thinking-1 — At Not published 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.
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 very strong math reasoning (aime 2025 97%, aime 2026 94.5%): MAI-Thinking-1 — 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.
MAI-Thinking-1: where it fits
Microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Released August 12, 2026 by Microsoft, it is built for very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%), microsoft's first in-house flagship reasoner, trained without OpenAI distillation, efficient reasoning at low token cost for its class, and competitive with Claude Opus 4.6 on SWE-Bench Pro (vendor-reported).
Its trade-offs: closed and in private preview — no open weights, no published pricing, thin availability, and benchmarks are largely self-reported.
The bottom line for this matchup
GPT-6 Luna and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; GPT-6 Luna holds the larger context; and each leads in its own area — GPT-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is GPT-6 Luna or MAI-Thinking-1 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-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 MAI-Thinking-1 leans toward very strong math reasoning (aime 2025 97%, aime 2026 94.5%), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Luna or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $0.1/$0.5 per 1M tokens vs Not published.
Which has the bigger context window?
GPT-6 Luna — 1.05M tokens vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-6 Luna and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Luna, MAI-Thinking-1 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, GPT-6 Luna or MAI-Thinking-1?
GPT-6 Luna — released September 22, 2026, about 41 days after MAI-Thinking-1.
GPT-6 Luna vs MAI-Thinking-1
OpenAI · US | Microsoft · US · Updated June 2026
Quick verdict
Pick GPT-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume or available to free and go plan users in the chatgpt desktop app, not gated to paid tiers. Pick MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%) or microsoft's first in-house flagship reasoner, trained without openai distillation. On a tight budget at scale, MAI-Thinking-1 is the value pick.
GPT-6 Luna (OpenAI) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. 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. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: GPT-6 Luna holds 4.1× more — 1.05M tokens (~1,575 pages) vs 256K (~384 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 41 days (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-6 Luna
MAI-Thinking-1
Provider
OpenAI (US)
Microsoft (US)
Released
September 22, 2026
August 12, 2026
Context window
1.05M tokens (~1,575 pages)
256K (~384 pages)
Price (in/out)
$0.1/$0.5 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
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 4.1× more than MAI-Thinking-1's 256K 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.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
GPT-6 Luna is comparatively weak here — less reasoning capability than sibling GPT-6 Sol — built for speed and volume, not hard problems
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
MAI-Thinking-1
GPT-6 Luna is comparatively weak here — as the entry-level tier, expect it to be the first model swapped out when OpenAI ships the next cost-tier refresh
Efficient reasoning at low token cost for its class
MAI-Thinking-1
MAI-Thinking-1 lists efficient reasoning at low token cost for its class among its strengths; GPT-6 Luna does not.
Lowest cost at scale
MAI-Thinking-1
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 4.1× larger than MAI-Thinking-1's 256K, fitting roughly 1,575 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-Thinking-1
At Not published 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.
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 very strong math reasoning (aime 2025 97%, aime 2026 94.5%)
→ MAI-Thinking-1
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.
MAI-Thinking-1: where it fits
Microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Released August 12, 2026 by Microsoft, it is built for very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%), microsoft's first in-house flagship reasoner, trained without OpenAI distillation, efficient reasoning at low token cost for its class, and competitive with Claude Opus 4.6 on SWE-Bench Pro (vendor-reported).
Its trade-offs: closed and in private preview — no open weights, no published pricing, thin availability, and benchmarks are largely self-reported.
The bottom line for this matchup
GPT-6 Luna and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; GPT-6 Luna holds the larger context; and each leads in its own area — GPT-6 Luna for openai's cheapest gpt-6 tier — $0.10/$0.50 per million tokens, optimized for fast responses at high volume, MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both GPT-6 Luna and MAI-Thinking-1 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.
Is GPT-6 Luna or MAI-Thinking-1 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-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 MAI-Thinking-1 leans toward very strong math reasoning (aime 2025 97%, aime 2026 94.5%), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-6 Luna or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $0.1/$0.5 per 1M tokens vs Not published.
Which has the bigger context window?
GPT-6 Luna — 1.05M tokens vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-6 Luna and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you GPT-6 Luna, MAI-Thinking-1 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, GPT-6 Luna or MAI-Thinking-1?
GPT-6 Luna — released September 22, 2026, about 41 days after MAI-Thinking-1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.