Model comparison
Gemma 4 31B vs MAI-Thinking-1
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 31B #43 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 31B and MAI-Thinking-1 share 2 comparable benchmark results. 2 of 8 categories are comparable. 27 results are unique to Gemma 4 31B; 11 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 2
- Gemma 4 31B only
- 27
- MAI-Thinking-1 only
- 11
- Comparable categories
- 2 / 8
Treat this as a split decision. Gemma 4 31B makes more sense if its workflow fits your team better; MAI-Thinking-1 is the better fit if coding is the priority.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Gemma 4 31B 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.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Gemma 4 31B | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Coding | Gemma 4 31B41.6 | Margin→ 23.9 | MAI-Thinking-165.5 |
| Knowledge | Gemma 4 31B52.9 | Margin→ 19.6 | MAI-Thinking-172.5 |
| Agentic | Gemma 4 31BNot measured | MarginNo overlap | MAI-Thinking-146.0 |
| Math | Gemma 4 31BNot measured | MarginNo overlap | MAI-Thinking-189.7 |
| Multimodal | Gemma 4 31B76.9 | MarginNo overlap | MAI-Thinking-1Not measured |
| Inst. Following | Gemma 4 31BNot measured | MarginNo overlap | MAI-Thinking-185.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 85.2%B 85%Winner: Gemma 4 31BΔ 0.2MMLU-Pro: Gemma 4 31B scored 85.2%; MAI-Thinking-1 scored 85%. Gemma 4 31B wins this benchmark. - Source ↗
GPQA
KnowledgeA 84.3%B 84.2%Winner: Gemma 4 31BΔ 0.1GPQA: Gemma 4 31B scored 84.3%; MAI-Thinking-1 scored 84.2%. Gemma 4 31B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 31B | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 31B$0 input / $0 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 31BNot available | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 31BNot available | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 31B256K | MAI-Thinking-1256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Gemma 4 31B | MAI-Thinking-1 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 14.4% | — | Not comparable |
| τ²-bench resultsSource | 59.9% | — | Not comparable |
| GDPval-AASource | 15.2% | — | Not comparable |
| GDPval-AASource | 804 | — | Not comparable |
| Gert LabsSource | 35.26% | — | Not comparable |
| AA EnterpriseOps-GymSource | 28.3% | — | Not comparable |
| AA ITBenchSource | 37.3% | — | Not comparable |
| AA Tau3 BankingSource | 15.1% | — | Not comparable |
| terminalBenchHardSource | 36.4% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 46% | Not comparable |
CodingMAI-Thinking-1 wins7 benchmarks
| Benchmark | Gemma 4 31B | MAI-Thinking-1 | Result |
|---|---|---|---|
| SWE-RebenchSource | 41.6% | — | Not comparable |
| React Native EvalsSource | 75.2% | — | Not comparable |
| AA Coding IndexSource | 43.4% | — | Not comparable |
| AA-SciCodeSource | 43.4% | — | Not comparable |
| SWE-bench VerifiedSource | — | 73.5% | Not comparable |
| SWE-bench ProSource | — | 52.8% | Not comparable |
| Terminal-Bench 2.0Source | — | 46.0% | Not comparable |
Reasoning3 benchmarks
KnowledgeMAI-Thinking-1 wins13 benchmarks
| Benchmark | Gemma 4 31B | MAI-Thinking-1 | Result |
|---|---|---|---|
| GPQASource | 84.3% | 84.2% | Gemma 4 31B leads |
| MMLU-ProSource | 85.2% | 85% | Gemma 4 31B leads |
| HLESource | 26.5% | — | Not comparable |
| HLE w/o toolsSource | 19.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 29.4% | — | Not comparable |
| AA-GPQA DiamondSource | 85.7% | — | Not comparable |
| AA-HLESource | 22.7% | — | Not comparable |
| AA-Omniscience IndexSource | -45.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 19.9% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 81.6% | — | Not comparable |
| AA Openness IndexSource | 38.9% | — | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
Math3 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (3)
Which is better, Gemma 4 31B or MAI-Thinking-1?
Gemma 4 31B 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 knowledge tasks, Gemma 4 31B or MAI-Thinking-1?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 52.9. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
Which is better for coding, Gemma 4 31B or MAI-Thinking-1?
MAI-Thinking-1 has the edge for coding in this comparison, averaging 65.5 versus 41.6. Gemma 4 31B stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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