Pick Gemini 3.5 Flash for speed — roughly 4x faster than rivals or cost — about a third the price. 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.
Gemini 3.5 Flash (Google) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. Gemini 3.5 Flash is google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. 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: Gemini 3.5 Flash holds 3.9× more — 1M (~1,500 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.
Specifications
Spec
Gemini 3.5 Flash
MAI-Thinking-1
Provider
Google (US)
Microsoft (US)
Released
May 19, 2026
June 2, 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$1.5/$9 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Speed — roughly 4x faster than rivals: Gemini 3.5 Flash — A core design strength of Gemini 3.5 Flash.
Cost — about a third the price: Gemini 3.5 Flash — A core design strength of Gemini 3.5 Flash.
Default in the Gemini app and Search AI Mode: Gemini 3.5 Flash — A core design strength of Gemini 3.5 Flash.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — A core design strength of MAI-Thinking-1.
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation: MAI-Thinking-1 — A core design strength of MAI-Thinking-1.
Efficient reasoning at low token cost for its class: MAI-Thinking-1 — A core design strength of MAI-Thinking-1.
Lowest cost at scale: MAI-Thinking-1 — At Not published, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Gemini 3.5 Flash — Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MAI-Thinking-1 — At Not published it undercuts Gemini 3.5 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.5 Flash — Larger 1M window fits more in one prompt.
Anyone whose priority is speed — roughly 4x faster than rivals: Gemini 3.5 Flash — 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.
Gemini 3.5 Flash: where it fits
Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. Released May 19, 2026 by Google, it is built for speed — roughly 4x faster than rivals, cost — about a third the price, default in the Gemini app and Search AI Mode, and high-volume multimodal work.
Its trade-offs are real: flash tier, not the deepest reasoning, and pro-tier 3.5 held back at launch. At $1.5 in / $9 out per million tokens, it sits in the mid 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 June 2, 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
Gemini 3.5 Flash and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; Gemini 3.5 Flash holds the larger context; and each leads in its own area — Gemini 3.5 Flash for speed — roughly 4x faster than rivals, 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 Gemini 3.5 Flash 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, Gemini 3.5 Flash leans toward speed — roughly 4x faster than rivals 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, Gemini 3.5 Flash or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $1.5/$9 per 1M tokens vs Not published.
Which has the bigger context window?
Gemini 3.5 Flash — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.5 Flash and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.5 Flash, 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, Gemini 3.5 Flash or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 14 days after Gemini 3.5 Flash.
Gemini 3.5 Flash vs MAI-Thinking-1
Google · US | Microsoft · US · Updated June 2026
Quick verdict
Pick Gemini 3.5 Flash for speed — roughly 4x faster than rivals or cost — about a third the price. 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.
Gemini 3.5 Flash (Google) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. Gemini 3.5 Flash is google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. 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: Gemini 3.5 Flash holds 3.9× more — 1M (~1,500 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.
Side-by-side specs
Spec
Gemini 3.5 Flash
MAI-Thinking-1
Provider
Google (US)
Microsoft (US)
Released
May 19, 2026
June 2, 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$1.5/$9 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Speed — roughly 4x faster than rivals
Gemini 3.5 Flash
A core design strength of Gemini 3.5 Flash.
Cost — about a third the price
Gemini 3.5 Flash
A core design strength of Gemini 3.5 Flash.
Default in the Gemini app and Search AI Mode
Gemini 3.5 Flash
A core design strength of Gemini 3.5 Flash.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
A core design strength of MAI-Thinking-1.
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
MAI-Thinking-1
A core design strength of MAI-Thinking-1.
Efficient reasoning at low token cost for its class
MAI-Thinking-1
A core design strength of MAI-Thinking-1.
Lowest cost at scale
MAI-Thinking-1
At Not published, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Gemini 3.5 Flash
Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-Thinking-1
At Not published it undercuts Gemini 3.5 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.5 Flash
Larger 1M window fits more in one prompt.
Anyone whose priority is speed — roughly 4x faster than rivals
→ Gemini 3.5 Flash
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.
Gemini 3.5 Flash: where it fits
Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. Released May 19, 2026 by Google, it is built for speed — roughly 4x faster than rivals, cost — about a third the price, default in the Gemini app and Search AI Mode, and high-volume multimodal work.
Its trade-offs are real: flash tier, not the deepest reasoning, and pro-tier 3.5 held back at launch. At $1.5 in / $9 out per million tokens, it sits in the mid 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 June 2, 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
Gemini 3.5 Flash and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; Gemini 3.5 Flash holds the larger context; and each leads in its own area — Gemini 3.5 Flash for speed — roughly 4x faster than rivals, 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 Gemini 3.5 Flash 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 Gemini 3.5 Flash 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, Gemini 3.5 Flash leans toward speed — roughly 4x faster than rivals 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, Gemini 3.5 Flash or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $1.5/$9 per 1M tokens vs Not published.
Which has the bigger context window?
Gemini 3.5 Flash — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.5 Flash and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.5 Flash, 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, Gemini 3.5 Flash or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 14 days after Gemini 3.5 Flash.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.