Model comparison
Gemini 3.1 Pro vs Kimi K2.6
Head-to-head evidence from 35 shared benchmark results across 7 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Gemini 3.1 Pro unranked; Kimi K2.6 #13
Evidence parity. Gemini 3.1 Pro and Kimi K2.6 share 35 comparable benchmark results. 2 of 8 categories are comparable. 13 results are unique to Gemini 3.1 Pro; 25 to Kimi K2.6.
Updated July 13, 2026- Shared results
- 35
- Gemini 3.1 Pro only
- 13
- Kimi K2.6 only
- 25
- Comparable categories
- 2 / 8
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Kimi K2.6 only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 35 shared benchmark results across 7 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Gemini 3.1 Pro is clearly ahead on the provisional aggregate, 88 to 74. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Pro's sharpest advantage is in multimodal & grounded, where it averages 82.6 against 79.8. The single biggest benchmark swing on the page is MMMU-Pro, 83.9% to 79.4%. Kimi K2.6 does hit back in mathematics, 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 $0.95 input / $4.00 output per 1M tokens for Kimi K2.6. That is roughly 3.0x on output cost alone. Kimi K2.6 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 256K for Kimi K2.6.
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 K2.6 |
|---|---|---|---|
| Math | Gemini 3.1 Pro31.8 | Margin→ 35.3 | Kimi K2.667.1 |
| Multimodal | Gemini 3.1 Pro82.6 | Margin← 2.8 | Kimi K2.679.8 |
| Agentic | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.673.5 |
| Coding | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.672.6 |
| Reasoning | Gemini 3.1 Pro77.1 | MarginNo overlap | Kimi K2.6Not measured |
| Knowledge | Gemini 3.1 ProNot measured | MarginNo overlap | Kimi K2.642.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMMU-Pro
MultimodalA 83.9%B 79.4%Winner: Gemini 3.1 ProΔ 4.5MMMU-Pro: Gemini 3.1 Pro scored 83.9%; Kimi K2.6 scored 79.4%. Gemini 3.1 Pro wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 16.700%B 14.580%Winner: Gemini 3.1 ProΔ 2.1FrontierMath v2 (Tier 4): Gemini 3.1 Pro scored 16.700%; Kimi K2.6 scored 14.580%. Gemini 3.1 Pro wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 36.900%B 38.966%Winner: Kimi K2.6Δ 2.1FrontierMath v2 (Tiers 1-3): Gemini 3.1 Pro scored 36.900%; Kimi K2.6 scored 38.966%. Kimi K2.6 wins this benchmark. - Source ↗
CharXiv
MultimodalA 80.2%B 80.4%Winner: Kimi K2.6Δ 0.2CharXiv: Gemini 3.1 Pro scored 80.2%; Kimi K2.6 scored 80.4%. Kimi K2.6 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 K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Pro$2 input / $12 output | Kimi K2.6$0.95 input / $4 output | Kimi K2.6 has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Pro109 tok/s | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.1 Pro29.71 s | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.1 Pro1M | Kimi K2.6256K | Gemini 3.1 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| Claw-EvalSource | 57.8% | 62.3% | Kimi K2.6 leads |
| DeepSearchQASource | 69.7% | 92.5% | Kimi K2.6 leads |
| Tau2-TelecomSource | 95.6% | 95.9% | Kimi K2.6 leads |
| AA Agentic IndexSource | 21.4% | 30.3% | Kimi K2.6 leads |
| APEX-Agents-AASource | 32.0% | 28.5% | Gemini 3.1 Pro leads |
| GDPval-AASource | 23.1% | 34.5% | Kimi K2.6 leads |
| GDPval-AASource | 962 | 1190 | Kimi K2.6 leads |
| Gert LabsSource | 56.87% | 56.82% | Gemini 3.1 Pro leads |
| ResearchClawBenchSource | 13.3% | 18.0% | Kimi K2.6 leads |
| AA AutomationBenchSource | 37.5% | 19.6% | Gemini 3.1 Pro leads |
| AA EnterpriseOps-GymSource | 42.2% | 38.5% | Gemini 3.1 Pro leads |
| AA Harvey LABSource | 0.0% | 0.0% | Tie |
| AA ITBenchSource | 30.3% | 31.2% | Kimi K2.6 leads |
| AA Tau3 BankingSource | 16.5% | 20.6% | Kimi K2.6 leads |
| Terminal-Bench 2.0Source | — | 66.7% | Not comparable |
| BrowseCompSource | — | 83.2% | Not comparable |
| OSWorld-VerifiedSource | — | 73.1% | Not comparable |
| ToolathlonSource | — | 50% | Not comparable |
| MCP AtlasSource | — | 55.9% | Not comparable |
| WideResearchSource | — | 80.8% | Not comparable |
| OSWorld 2.0Source | — | 4.6% | Not comparable |
| AA BriefcaseSource | — | 809 | Not comparable |
Coding15 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| LiveCodeBench ProSource | 82.9% | — | Not comparable |
| React Native EvalsSource | 78.9% | — | Not comparable |
| Vibe Code BenchSource | 32.03% | 37.89% | Kimi K2.6 leads |
| AA Coding IndexSource | 68.8% | 61.8% | Gemini 3.1 Pro leads |
| Terminal-Bench HardSource | 53.8% | 43.9% | Gemini 3.1 Pro leads |
| AA-SciCodeSource | 58.9% | 53.5% | Gemini 3.1 Pro leads |
| AA Terminal-Bench 2.1Source | 73.8% | 65.9% | Gemini 3.1 Pro leads |
| SWE-bench VerifiedSource | — | 80.2% | Not comparable |
| LiveCodeBenchSource | — | 89.6% | Not comparable |
| LiveCodeBench v6Source | — | 89.6% | Not comparable |
| SWE-bench ProSource | — | 58.6% | Not comparable |
| SWE MultilingualSource | — | 76.7% | Not comparable |
| SciCodeSource | — | 52.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 66.7% | Not comparable |
| cursorBench31Source | — | 47.6% | Not comparable |
Reasoning3 benchmarks
Knowledge13 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| GPQA-DSource | 94.3% | 90.5% | 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% | 44.2% | Gemini 3.1 Pro leads |
| AA-GPQA DiamondSource | 94.1% | 91.1% | Gemini 3.1 Pro leads |
| AA-HLESource | 44.7% | 35.9% | Gemini 3.1 Pro leads |
| AA-Omniscience IndexSource | 32.9% | 6.4% | Gemini 3.1 Pro leads |
| AA-Omniscience AccuracySource | 55.3% | 32.8% | Gemini 3.1 Pro leads |
| AA-Omniscience Hallucination RateSource | 49.9% | 39.3% | Kimi K2.6 leads |
| GPQASource | — | 90.5% | Not comparable |
| HLESource | — | 34.7% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
MathKimi K2.6 wins5 benchmarks
Multilingual1 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 93.2% | — | Not comparable |
MultimodalGemini 3.1 Pro wins13 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| MMMU-ProSource | 83.9% | 79.4% | Gemini 3.1 Pro leads |
| CharXivSource | 80.2% | 80.4% | Kimi K2.6 leads |
| 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 |
| GDPval-AASource | 1320 | — | Not comparable |
| AA-MMMU-ProSource | 82.4% | 79.4% | Gemini 3.1 Pro leads |
| Design Arena WebsiteSource | 1294 | 1318 | Kimi K2.6 leads |
| MMMU-Pro w/ PythonSource | — | 80.1% | Not comparable |
| MathVisionSource | — | 87.4% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Gemini 3.1 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.1% | 76.0% | Gemini 3.1 Pro leads |
Frequently Asked Questions (3)
Which is better, Gemini 3.1 Pro or Kimi K2.6?
Gemini 3.1 Pro is ahead on BenchLM's provisional leaderboard, 88 to 74. The biggest single separator in this matchup is MMMU-Pro, where the scores are 83.9% and 79.4%.
Which is better for math, Gemini 3.1 Pro or Kimi K2.6?
Kimi K2.6 has the edge for math in this comparison, averaging 67.1 versus 31.8. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Gemini 3.1 Pro or Kimi K2.6?
Gemini 3.1 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 82.6 versus 79.8. Inside this category, Design Arena Website 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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