Model comparison
Gemini 3.1 Pro vs Kimi K2.5 (Reasoning)
Head-to-head evidence from 21 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3.1 Pro #83 (Estimated); Kimi K2.5 (Reasoning) #57 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.1 Pro and Kimi K2.5 (Reasoning) share 21 comparable benchmark results. 1 of 8 categories are comparable. 26 results are unique to Gemini 3.1 Pro; 6 to Kimi K2.5 (Reasoning).
Updated July 20, 2026- Shared results
- 21
- Gemini 3.1 Pro only
- 26
- Kimi K2.5 (Reasoning) only
- 6
- Comparable categories
- 1 / 8
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemini 3.1 Pro only becomes the better choice if multimodal & grounded is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 21 shared benchmark results across 6 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
Kimi K2.5 (Reasoning) is clearly ahead on the BenchAlign aggregate, 59.35 to 55.3. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Pro is also the more expensive model on tokens at $2.00 input / $12.00 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5 (Reasoning). That is roughly 4.0x on output cost alone. Kimi K2.5 (Reasoning) is the reasoning model in the pair, while Gemini 3.1 Pro 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 3.1 Pro gives you the larger context window at 1M, compared with 128K for Kimi K2.5 (Reasoning).
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 | Gemini 3.1 Pro | Δ | Kimi K2.5 (Reasoning) |
|---|---|---|---|
| Multimodal | Gemini 3.1 Pro82.6 | Margin← 4.1 | Kimi K2.5 (Reasoning)78.5 |
| Agentic | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.5 (Reasoning)55.0 |
| Coding | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.5 (Reasoning)76.8 |
| Reasoning | Gemini 3.1 Pro77.1 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Knowledge | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.5 (Reasoning)87.2 |
| Math | Gemini 3.1 Pro31.8 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMMU-Pro
MultimodalA 83.9%B 78.5%Winner: Gemini 3.1 ProΔ 5.4MMMU-Pro: Gemini 3.1 Pro scored 83.9%; Kimi K2.5 (Reasoning) scored 78.5%. Gemini 3.1 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.1 Pro | Kimi K2.5 (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Pro$2 input / $12 output | Kimi K2.5 (Reasoning)$0.6 input / $3 output | Kimi K2.5 (Reasoning) has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Pro109 tok/s | Kimi K2.5 (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.1 Pro29.71 s | Kimi K2.5 (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.1 Pro1M | Kimi K2.5 (Reasoning)128K | Gemini 3.1 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic18 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| Claw-EvalSource | 57.8% | — | Not comparable |
| DeepSearchQASource | 69.7% | — | Not comparable |
| τ²-bench resultsSource | 95.6% | 95.9% | Kimi K2.5 (Reasoning) leads |
| AA Agentic IndexSource | 21.4% | 21.7% | Kimi K2.5 (Reasoning) leads |
| APEX-Agents-AASource | 32.0% | 11.5% | Gemini 3.1 Pro leads |
| GDPval-AASource | 23.2% | 25.4% | Kimi K2.5 (Reasoning) leads |
| GDPval-AASource | 965 | 1009 | Kimi K2.5 (Reasoning) leads |
| Gert LabsSource | 56.87% | 32.58% | Gemini 3.1 Pro leads |
| ResearchClawBenchSource | 13.3% | — | Not comparable |
| AA AutomationBenchSource | 37.5% | — | Not comparable |
| AA EnterpriseOps-GymSource | 42.2% | — | Not comparable |
| AA Harvey LABSource | 0.0% | — | Not comparable |
| AA ITBenchSource | 30.3% | — | Not comparable |
| AA Tau3 BankingSource | 16.5% | — | Not comparable |
| terminalBenchHardSource | 53.8% | — | Not comparable |
| aaTerminalBench21Source | 73.8% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 50.8% | Not comparable |
| BrowseCompSource | — | 60.6% | Not comparable |
Coding6 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| LiveCodeBench ProSource | 82.9% | — | Not comparable |
| React Native EvalsSource | 78.9% | — | Not comparable |
| Vibe Code BenchSource | 32.03% | 17.54% | Gemini 3.1 Pro leads |
| AA Coding IndexSource | 68.8% | 46.8% | Gemini 3.1 Pro leads |
| AA-SciCodeSource | 58.9% | 49.0% | Gemini 3.1 Pro leads |
| SWE-bench VerifiedSource | — | 76.8% | Not comparable |
Reasoning3 benchmarks
Knowledge12 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| GPQA-DSource | 94.3% | — | Not comparable |
| HLE w/o toolsSource | 45.4% | — | Not comparable |
| HealthBench HardSource | 20.6% | — | Not comparable |
| MedXpertQA (Text)Source | 71.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 46.5% | 35.4% | Gemini 3.1 Pro leads |
| AA-GPQA DiamondSource | 94.1% | 87.9% | Gemini 3.1 Pro leads |
| AA-HLESource | 44.7% | 29.4% | Gemini 3.1 Pro leads |
| AA-Omniscience IndexSource | 32.9% | -8.1% | Gemini 3.1 Pro leads |
| AA-Omniscience AccuracySource | 55.3% | 34.3% | Gemini 3.1 Pro leads |
| AA-Omniscience Hallucination RateSource | 49.9% | 64.6% | Gemini 3.1 Pro leads |
| GPQASource | — | 87.6% | Not comparable |
| MMLU-ProSource | — | 87.1% | Not comparable |
Math3 benchmarks
Multilingual1 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 93.2% | — | Not comparable |
MultimodalGemini 3.1 Pro wins9 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| MMMU-ProSource | 83.9% | 78.5% | Gemini 3.1 Pro leads |
| CharXivSource | 80.2% | — | Not comparable |
| ERQASource | 69.4% | — | Not comparable |
| SimpleVQASource | 72.4% | — | Not comparable |
| ScreenSpot ProSource | 84.4% | — | Not comparable |
| ZeroBenchSource | 29.0% | — | Not comparable |
| MedXpertQA (MM)Source | 81.3% | — | Not comparable |
| AA-MMMU-ProSource | 82.4% | 75.4% | Gemini 3.1 Pro leads |
| Design Arena WebsiteSource | 1284 | 1282 | Gemini 3.1 Pro leads |
Inst. Following1 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.1% | 70.2% | Gemini 3.1 Pro leads |
Frequently Asked Questions (2)
Which is better, Gemini 3.1 Pro or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) is ahead on BenchLM's BenchAlign leaderboard, 59.35 to 55.3. The biggest single separator in this matchup is MMMU-Pro, where the scores are 83.9% and 78.5%.
Which is better for multimodal and grounded tasks, Gemini 3.1 Pro or Kimi K2.5 (Reasoning)?
Gemini 3.1 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 82.6 versus 78.5. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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.