Model comparison
Gemini 3.1 Pro vs Kimi K2.5
Head-to-head evidence from 27 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3.1 Pro #83 (Estimated); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.1 Pro and Kimi K2.5 share 27 comparable benchmark results. 3 of 8 categories are comparable. 20 results are unique to Gemini 3.1 Pro; 36 to Kimi K2.5.
Updated July 20, 2026- Shared results
- 27
- Gemini 3.1 Pro only
- 20
- Kimi K2.5 only
- 36
- Comparable categories
- 3 / 8
Pick Kimi K2.5 if you want the stronger benchmark profile. Gemini 3.1 Pro only becomes the better choice if reasoning is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 27 shared benchmark results across 7 evidence categories; 3 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 is clearly ahead on the BenchAlign aggregate, 59.66 to 55.3. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5's sharpest advantage is in mathematics, where it averages 60.6 against 31.8. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 16.700% to 4.200%. Gemini 3.1 Pro does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
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. That is roughly 4.0x on output cost alone. Gemini 3.1 Pro gives you the larger context window at 1M, compared with 256K for Kimi K2.5.
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 |
|---|---|---|---|
| Math | Gemini 3.1 Pro31.8 | Margin→ 28.8 | Kimi K2.560.6 |
| Reasoning | Gemini 3.1 Pro77.1 | Margin← 16.1 | Kimi K2.561.0 |
| Multimodal | Gemini 3.1 Pro82.6 | Margin← 4.1 | Kimi K2.578.5 |
| Agentic | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.555.0 |
| Coding | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.559.4 |
| Knowledge | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.556.9 |
| Multilingual | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.582.3 |
| Inst. Following | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.593.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 16.700%B 4.200%Winner: Gemini 3.1 ProΔ 12.5FrontierMath v2 (Tier 4): Gemini 3.1 Pro scored 16.700%; Kimi K2.5 scored 4.200%. Gemini 3.1 Pro wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 36.900%B 27.900%Winner: Gemini 3.1 ProΔ 9FrontierMath v2 (Tiers 1-3): Gemini 3.1 Pro scored 36.900%; Kimi K2.5 scored 27.900%. Gemini 3.1 Pro wins this benchmark. - 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 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 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Pro$2 input / $12 output | Kimi K2.5$0.6 input / $3 output | Kimi K2.5 has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Pro109 tok/s | Kimi K2.545 tok/s | Gemini 3.1 Pro has the higher measured throughput. |
| First-answer latencyseconds to first token | Gemini 3.1 Pro29.71 s | Kimi K2.52.38 s | Kimi K2.5 reaches the first token sooner. |
| Context windowmaximum listed tokens | Gemini 3.1 Pro1M | Kimi K2.5256K | Gemini 3.1 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic26 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 | Result |
|---|---|---|---|
| Claw-EvalSource | 57.8% | 52.3% | Gemini 3.1 Pro leads |
| DeepSearchQASource | 69.7% | 77.1% | Kimi K2.5 leads |
| τ²-bench resultsSource | 95.6% | 95.9% | Kimi K2.5 leads |
| AA Agentic IndexSource | 21.4% | 21.7% | Kimi K2.5 leads |
| APEX-Agents-AASource | 32.0% | 11.5% | Gemini 3.1 Pro leads |
| GDPval-AASource | 23.2% | 25.4% | Kimi K2.5 leads |
| GDPval-AASource | 965 | 1009 | Kimi K2.5 leads |
| Gert LabsSource | 56.87% | 45.88% | Gemini 3.1 Pro leads |
| ResearchClawBenchSource | 13.3% | 14.0% | Kimi K2.5 leads |
| 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 |
| QwenClawBenchSource | — | 54.3% | Not comparable |
| τ³-bench resultsSource | — | 65.7% | Not comparable |
| DeepPlanningSource | — | 14.4% | Not comparable |
| ToolathlonSource | — | 27.8% | Not comparable |
| MCP AtlasSource | — | 29.5% | Not comparable |
| MCP-TasksSource | — | 59.1% | Not comparable |
| WideResearchSource | — | 72.7% | Not comparable |
| JobBenchSource | — | 8.7% | Not comparable |
Coding12 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 | Result |
|---|---|---|---|
| LiveCodeBench ProSource | 82.9% | — | Not comparable |
| React Native EvalsSource | 78.9% | 77.2% | Gemini 3.1 Pro leads |
| Vibe Code BenchSource | 32.03% | — | Not comparable |
| 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 |
| SWE-bench Verified*Source | — | 70.8% | Not comparable |
| LiveCodeBench v6Source | — | 85.0% | Not comparable |
| SWE-bench ProSource | — | 50.7% | Not comparable |
| SWE MultilingualSource | — | 73% | Not comparable |
| SWE-RebenchSource | — | 58.5% | Not comparable |
| SciCodeSource | — | 48.7% | Not comparable |
ReasoningGemini 3.1 Pro wins4 benchmarks
Knowledge15 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 | Result |
|---|---|---|---|
| GPQA-DSource | 94.3% | 87.6% | Gemini 3.1 Pro leads |
| 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 |
| SuperGPQASource | — | 69.2% | Not comparable |
| MMLU-ProSource | — | 87.1% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 87.1% | Not comparable |
| HLESource | — | 30.1% | Not comparable |
MathKimi K2.5 wins9 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 36.900% | 27.900% | Gemini 3.1 Pro leads |
| FrontierMath v2 (Tier 4)Source | 16.700% | 4.200% | Gemini 3.1 Pro leads |
| AIME 2025Source | — | 96.1% | Not comparable |
| AIME26Source | — | 95.8% | Not comparable |
| AIME25 (Arcee)Source | — | 96.3% | Not comparable |
| HMMT Feb 2025Source | — | 95.4% | Not comparable |
| HMMT Nov 2025Source | — | 91.1% | Not comparable |
| HMMT Feb 2026Source | — | 87.1% | Not comparable |
| MMAnswerBenchSource | — | 81.8% | Not comparable |
Multilingual3 benchmarks
MultimodalGemini 3.1 Pro wins12 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.5 | 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 |
| Video-MMESource | — | 87.4% | Not comparable |
| MMVUSource | — | 80.4% | Not comparable |
| VideoMMMUSource | — | 86.6% | Not comparable |
Frequently Asked Questions (4)
Which is better, Gemini 3.1 Pro or Kimi K2.5?
Kimi K2.5 is ahead on BenchLM's BenchAlign leaderboard, 59.66 to 55.3. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 16.700% and 4.200%.
Which is better for math, Gemini 3.1 Pro or Kimi K2.5?
Kimi K2.5 has the edge for math in this comparison, averaging 60.6 versus 31.8. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
Which is better for reasoning, Gemini 3.1 Pro or Kimi K2.5?
Gemini 3.1 Pro has the edge for reasoning in this comparison, averaging 77.1 versus 61. Inside this category, CritPt is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Gemini 3.1 Pro or Kimi K2.5?
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.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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