Both are Microsoft models. MAI-Thinking-1 is the newer, generally stronger default; reach for MAI-1-preview when a specific cost or latency profile matters more than the latest capabilities.
MAI-1-preview and MAI-Thinking-1 are both Microsoft models, so the real question is not which lab to trust but which tier fits your workload and budget. 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. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Context window: MAI-Thinking-1 holds 2× more — 256K (~384 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: MAI-Thinking-1 is the newer model by about 12 months (released August 12, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
MAI-1-preview
MAI-Thinking-1
Provider
Microsoft (US)
Microsoft (US)
Released
August 28, 2025
August 12, 2026
Context window
128K (~192 pages)
256K (~384 pages)
Price (in/out)
Not published
Not published
Open weight?
No — API only
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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; MAI-Thinking-1 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; MAI-Thinking-1 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; MAI-Thinking-1 does not.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation: MAI-Thinking-1 — MAI-1-preview is comparatively weak here — a 'preview' release, not yet positioned as Microsoft's primary Copilot model
Efficient reasoning at low token cost for its class: MAI-Thinking-1 — Its 256K window holds about 2× more than MAI-1-preview's 128K in a single prompt.
Largest single-prompt input: MAI-Thinking-1 — Its 256K window is about 2× larger than MAI-1-preview's 128K, fitting roughly 384 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases: MAI-Thinking-1 — Larger 256K window fits more in one prompt.
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 — 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.
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 are real: 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.
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
Because MAI-1-preview and MAI-Thinking-1 come from the same lab (Microsoft), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. MAI-Thinking-1 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 MAI-Thinking-1 and drop down only with a concrete reason.
Frequently asked questions
Is MAI-1-preview 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, MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai 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, MAI-1-preview or MAI-Thinking-1?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
MAI-Thinking-1 — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from MAI-1-preview to MAI-Thinking-1?
Since both are Microsoft models, the newer one (MAI-Thinking-1) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, MAI-1-preview or MAI-Thinking-1?
MAI-Thinking-1 — released August 12, 2026, about 12 months after MAI-1-preview.
MAI-1-preview vs MAI-Thinking-1
Microsoft · US | Microsoft · US · Updated June 2026
Quick verdict
Both are Microsoft models. MAI-Thinking-1 is the newer, generally stronger default; reach for MAI-1-preview when a specific cost or latency profile matters more than the latest capabilities.
MAI-1-preview and MAI-Thinking-1 are both Microsoft models, so the real question is not which lab to trust but which tier fits your workload and budget. 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. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. 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
▸Context window: MAI-Thinking-1 holds 2× more — 256K (~384 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: MAI-Thinking-1 is the newer model by about 12 months (released August 12, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
MAI-1-preview
MAI-Thinking-1
Provider
Microsoft (US)
Microsoft (US)
Released
August 28, 2025
August 12, 2026
Context window
128K (~192 pages)
256K (~384 pages)
Price (in/out)
Not published
Not published
Open weight?
No — API only
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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; MAI-Thinking-1 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; MAI-Thinking-1 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; MAI-Thinking-1 does not.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
MAI-Thinking-1
MAI-1-preview is comparatively weak here — a 'preview' release, not yet positioned as Microsoft's primary Copilot model
Efficient reasoning at low token cost for its class
MAI-Thinking-1
Its 256K window holds about 2× more than MAI-1-preview's 128K in a single prompt.
Largest single-prompt input
MAI-Thinking-1
Its 256K window is about 2× larger than MAI-1-preview's 128K, fitting roughly 384 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ MAI-Thinking-1
Larger 256K window fits more in one prompt.
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
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.
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 are real: 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.
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
Because MAI-1-preview and MAI-Thinking-1 come from the same lab (Microsoft), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. MAI-Thinking-1 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 MAI-Thinking-1 and drop down only with a concrete reason.
Want both MAI-1-preview 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 MAI-1-preview 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, MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai 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, MAI-1-preview or MAI-Thinking-1?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
MAI-Thinking-1 — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from MAI-1-preview to MAI-Thinking-1?
Since both are Microsoft models, the newer one (MAI-Thinking-1) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, MAI-1-preview or MAI-Thinking-1?
MAI-Thinking-1 — released August 12, 2026, about 12 months after MAI-1-preview.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.