Gemini 3.7 Flash vs MAI-Thinking-1
Google · US | Microsoft · US · Updated June 2026
Quick verdict
Pick Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing or 1m-token context with full multimodal input (text, image, audio, video). 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 3.7 Flash (Google) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. Gemini 3.7 Flash is google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. 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 3.7 Flash holds 4.1× more — 1M (~1,573 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 3.7 Flash | MAI-Thinking-1 |
|---|---|---|
| Provider | Google (US) | Microsoft (US) |
| Released | August 13, 2026 | August 12, 2026 |
| Context window | 1M (~1,573 pages) | 256K (~384 pages) |
| Price (in/out) | $0.75/$3.75 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
Strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing
Gemini 3.7 Flash
MAI-Thinking-1 is comparatively weak here — closed and in private preview — no open weights, no published pricing, thin availability
1M-token context with full multimodal input (text, image, audio, video)
Gemini 3.7 Flash
Its 1M window holds about 4.1× more than MAI-Thinking-1's 256K in a single prompt.
Built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra
Gemini 3.7 Flash
Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed — and it carries the larger 1M context.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
MAI-Thinking-1 lists very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%) among its strengths; Gemini 3.7 Flash does not.
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
MAI-Thinking-1
Gemini 3.7 Flash is comparatively weak here — a fast 'workhorse,' not Google's top-intelligence model (Gemini 3.1 Pro is still the flagship)
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; Gemini 3.7 Flash does not.
Lowest cost at scale
MAI-Thinking-1
Its weights are open, so at volume you pay for your own hardware instead of Gemini 3.7 Flash's $0.75/$3.75 per 1M tokens.
Largest single-prompt input
Gemini 3.7 Flash
Its 1M window is about 4.1× larger than MAI-Thinking-1's 256K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-Thinking-1
At Not published it undercuts Gemini 3.7 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.7 Flash
Larger 1M window fits more in one prompt.
Anyone whose priority is strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing
→ Gemini 3.7 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 3.7 Flash: where it fits
Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. Released August 13, 2026 by Google, it is built for strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing, 1M-token context with full multimodal input (text, image, audio, video), built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra, and wins broad-coding and web-development benchmarks against GPT-5.6 Terra.
Its trade-offs are real: introductory pricing ($0.75/$3.75) reverts to $1.50/$7.50 on Jan 1, 2027, trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding, a fast 'workhorse,' not Google's top-intelligence model (Gemini 3.1 Pro is still the flagship), and some benchmark gains are Google's own figures. At $0.75 in / $3.75 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
Gemini 3.7 Flash and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; Gemini 3.7 Flash holds the larger context; and each leads in its own area — Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing, 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 3.7 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.
See pricingFrequently asked questions
Is Gemini 3.7 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 3.7 Flash leans toward strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing 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 3.7 Flash or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $0.75/$3.75 per 1M tokens vs Not published.
Which has the bigger context window?
Gemini 3.7 Flash — 1M 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 Gemini 3.7 Flash and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.7 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 3.7 Flash or MAI-Thinking-1?
Gemini 3.7 Flash — released August 13, 2026, about 1 days after MAI-Thinking-1.
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.