GPT-6 Sol vs MAI-1-preview

OpenAI · US  |  Microsoft · US · Updated June 2026

Quick verdict

Pick GPT-6 Sol 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 or openai says it makes about half as many mistakes as gpt-5.6 sol. Pick MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. On a tight budget at scale, MAI-1-preview is the value pick.

GPT-6 Sol (OpenAI) and MAI-1-preview (Microsoft) are two of the models people most often weigh against each other in 2026. 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. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGPT-6 SolMAI-1-preview
ProviderOpenAI (US) Microsoft (US)
ReleasedSeptember 22, 2026 August 28, 2025
Context window1.05M tokens (~1,575 pages) 128K (~192 pages)
Price (in/out)$2/$10 per 1M tokens Not published
Open weight?No — API only No — API only
Modalitiestext, image text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

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

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 carries the larger 1.05M tokens context.

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; MAI-1-preview does not.

Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI

MAI-1-preview

MAI-1-preview lists microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI among its strengths; GPT-6 Sol does not.

Ranked in the top 15 on LM Arena at launch

MAI-1-preview

MAI-1-preview lists ranked in the top 15 on LM Arena at launch among its strengths; GPT-6 Sol does not.

Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment

MAI-1-preview

MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment among its strengths; GPT-6 Sol does not.

Lowest cost at scale

MAI-1-preview

Its weights are open, so at volume you pay for your own hardware instead of GPT-6 Sol's $2/$10 per 1M tokens.

Largest single-prompt input

GPT-6 Sol

Its 1.05M tokens window is about 8.2× larger than MAI-1-preview's 128K, fitting roughly 1,575 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

MAI-1-preview

At Not published 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 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

It is specifically built for that.

Anyone whose priority is microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai

MAI-1-preview

That is its strongest area.

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 are real: 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.

MAI-1-preview: where it fits

Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.

Its trade-offs: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.

The bottom line for this matchup

GPT-6 Sol and MAI-1-preview overlap enough that the right pick depends on your specific job. MAI-1-preview costs less per token; GPT-6 Sol holds the larger context; and each leads in its own area — GPT-6 Sol 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, MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai. Rather than crowning one, run the same hard task through both once and let the results decide.

Want both GPT-6 Sol and MAI-1-preview 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.

See pricing

Frequently asked questions

Is GPT-6 Sol or MAI-1-preview 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 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 while MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GPT-6 Sol or MAI-1-preview?

MAI-1-preview is cheaper — $2/$10 per 1M tokens vs Not published.

Which has the bigger context window?

GPT-6 Sol — 1.05M tokens vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GPT-6 Sol and MAI-1-preview together?

Yes — a multi-model platform like LumiChats gives you GPT-6 Sol, MAI-1-preview 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 Sol or MAI-1-preview?

GPT-6 Sol — released September 22, 2026, about 13 months after MAI-1-preview.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.