Model comparison
Gemini 3 Flash vs MAI-Thinking-1
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3 Flash #49 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3 Flash and MAI-Thinking-1 share 0 comparable benchmark results. 1 of 8 categories are comparable. 19 results are unique to Gemini 3 Flash; 13 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 0
- Gemini 3 Flash only
- 19
- MAI-Thinking-1 only
- 13
- Comparable categories
- 1 / 8
Treat this as a split decision. Gemini 3 Flash makes more sense if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model; MAI-Thinking-1 is the better fit if mathematics is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Gemini 3 Flash and MAI-Thinking-1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
MAI-Thinking-1 is the reasoning model in the pair, while Gemini 3 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 3 Flash gives you the larger context window at 1M, compared with 256K for MAI-Thinking-1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3 Flash | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3 Flash$0.5 input / $3 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemini 3 Flash159 tok/s | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3 Flash1.19 s | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3 Flash1M | MAI-Thinking-1256K | Gemini 3 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding5 benchmarks
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | Gemini 3 Flash | MAI-Thinking-1 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 27.4% | — | Not comparable |
| AA-GPQA DiamondSource | 81.2% | — | Not comparable |
| AA-HLESource | 14.1% | — | Not comparable |
| AA-Omniscience IndexSource | -3.6% | — | Not comparable |
| AA-Omniscience AccuracySource | 45.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 90.2% | — | Not comparable |
| GPQASource | — | 84.2% | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
| MMLU-ProSource | — | 85% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
MathMAI-Thinking-1 wins5 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (2)
Which is better, Gemini 3 Flash or MAI-Thinking-1?
Gemini 3 Flash and MAI-Thinking-1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for math, Gemini 3 Flash or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 27.8. Gemini 3 Flash stays close enough that the answer can still flip depending on your workload.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.