Model comparison
Gemini 3 Pro vs Kimi K3
Head-to-head evidence from 14 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3 Pro #19 (Supported); Kimi K3 #4 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3 Pro and Kimi K3 share 14 comparable benchmark results. 1 of 8 categories are comparable. 13 results are unique to Gemini 3 Pro; 43 to Kimi K3.
Updated July 23, 2026- Shared results
- 14
- Gemini 3 Pro only
- 13
- Kimi K3 only
- 43
- Comparable categories
- 1 / 8
Pick Kimi K3 if you want the stronger benchmark profile. Gemini 3 Pro only becomes the better choice if multimodal & grounded is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 5 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 K3 is clearly ahead on the BenchAlign aggregate, 80.96 to 67.73. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K3 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $2.00 input / $12.00 output per 1M tokens for Gemini 3 Pro. Kimi K3 is the reasoning model in the pair, while Gemini 3 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 Pro gives you the larger context window at 2M, compared with 1.05M for Kimi K3.
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 Pro | Δ | Kimi K3 |
|---|---|---|---|
| Multimodal | Gemini 3 Pro81.1 | Margin← 2.6 | Kimi K378.5 |
| Agentic | Gemini 3 ProNot measured | MarginNo overlap | Kimi K389.5 |
| Reasoning | Gemini 3 Pro31.1 | MarginNo overlap | Kimi K3Not measured |
| Knowledge | Gemini 3 ProNot measured | MarginNo overlap | Kimi K361.0 |
| Math | Gemini 3 Pro32.9 | MarginNo overlap | Kimi K3Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3 Pro | Kimi K3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3 Pro$2 input / $12 output | Kimi K3$3 input / $15 output | Gemini 3 Pro has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3 Pro109 tok/s | Kimi K3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3 Pro32.65 s | Kimi K3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3 Pro2M | Kimi K31.05M | Gemini 3 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic23 benchmarks
| Benchmark | Gemini 3 Pro | Kimi K3 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 87.1% | — | Not comparable |
| Gert LabsSource | 63.23% | — | Not comparable |
| JobBenchSource | 11.4% | 52.9% | Kimi K3 leads |
| Terminal-Bench 2.0Source | — | 88.3% | Not comparable |
| BrowseCompSource | — | 91.2% | Not comparable |
| DeepSearchQASource | — | 95.0% | Not comparable |
| Toolathlon-VerifiedSource | — | 73.2% | Not comparable |
| MCP AtlasSource | — | 84.2% | Not comparable |
| AutomationBenchSource | — | 30.8% | Not comparable |
| APEX-AgentsSource | — | 37.6% | Not comparable |
| SpreadsheetBench 2Source | — | 34.8% | Not comparable |
| DECK-BenchSource | — | 73.5% | Not comparable |
| AA Agentic IndexSource | — | 50.1% | Not comparable |
| GDPval-AASource | — | 59.0% | Not comparable |
| GDPval-AASource | — | 1679 | Not comparable |
| AA BriefcaseSource | — | 1543 | Not comparable |
| AA AutomationBenchSource | — | 52.7% | Not comparable |
| AA EnterpriseOps-GymSource | — | 45.3% | Not comparable |
| AA Harvey LABSource | — | 94.6% | Not comparable |
| AA Tau3 BankingSource | — | 33.4% | Not comparable |
| aaTerminalBench21Source | — | 85% | Not comparable |
| APEX-Agents-AASource | — | 41.3% | Not comparable |
| AA ITBenchSource | — | 47.7% | Not comparable |
Coding11 benchmarks
| Benchmark | Gemini 3 Pro | Kimi K3 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 14.30% | — | Not comparable |
| AA-SciCodeSource | 56.1% | 58.7% | Kimi K3 leads |
| AA LiveCodeBenchSource | 91.7% | — | Not comparable |
| deepSweSource | — | 67.5% | Not comparable |
| FrontierSWESource | — | 81.2% | Not comparable |
| ProgramBenchSource | — | 77.8% | Not comparable |
| Kimi Code Bench v2Source | — | 72.9% | Not comparable |
| sweMarathonSource | — | 42% | Not comparable |
| PostTrain BenchSource | — | 36.6% | Not comparable |
| MLS-Bench LiteSource | — | 48.3% | Not comparable |
| AA Coding IndexSource | — | 76.2% | Not comparable |
Reasoning3 benchmarks
Knowledge11 benchmarks
| Benchmark | Gemini 3 Pro | Kimi K3 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 39.5% | 57.1% | Kimi K3 leads |
| AA-GPQA DiamondSource | 90.8% | 93.5% | Kimi K3 leads |
| AA-HLESource | 37.2% | 44.3% | Kimi K3 leads |
| AA-Omniscience IndexSource | 15.8% | 18.4% | Kimi K3 leads |
| AA-Omniscience AccuracySource | 55.9% | 46.0% | Gemini 3 Pro leads |
| AA-Omniscience Hallucination RateSource | 90.9% | 50.9% | Kimi K3 leads |
| AA MMLU-ProSource | 89.8% | — | Not comparable |
| GPQASource | — | 93.5% | Not comparable |
| GPQA-DSource | — | 93.5% | Not comparable |
| HLESource | — | 56% | Not comparable |
| HLE w/o toolsSource | — | 43.5% | Not comparable |
Math2 benchmarks
Multilingual1 benchmarks
| Benchmark | Gemini 3 Pro | Kimi K3 | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | 92.2% | — | Not comparable |
MultimodalGemini 3 Pro wins18 benchmarks
| Benchmark | Gemini 3 Pro | Kimi K3 | Result |
|---|---|---|---|
| MMMU-ProSource | 81% | 81.6% | Kimi K3 leads |
| MathVisionSource | 86.6% | 94.3% | Kimi K3 leads |
| VideoMMMUSource | 87.6% | — | Not comparable |
| ScreenSpot ProSource | 72.7% | — | Not comparable |
| CharXivSource | 81.4% | 91.3% | Kimi K3 leads |
| V*Source | 88.0% | — | Not comparable |
| AA-MMMU-ProSource | 80.2% | 80.5% | Kimi K3 leads |
| OfficeQA ProSource | — | 63.3% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 83.4% | Not comparable |
| CharXiv w/o toolsSource | — | 84.8% | Not comparable |
| MathVision w/ PythonSource | — | 97.8% | Not comparable |
| BabyVision w/ PythonSource | — | 85.7% | Not comparable |
| ZeroBenchSource | — | 23.0% | Not comparable |
| ZeroBench w/ PythonSource | — | 41.0% | Not comparable |
| WorldVQA ForceAnswerSource | — | 51.0% | Not comparable |
| OmniDocBenchSource | — | 91.1% | Not comparable |
| PerceptionBenchSource | — | 58.5% | Not comparable |
| Design Arena WebsiteSource | — | 1386 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Gemini 3 Pro | Kimi K3 | Result |
|---|---|---|---|
| AA-IFBenchSource | 70.4% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, Gemini 3 Pro or Kimi K3?
Kimi K3 is ahead on BenchLM's BenchAlign leaderboard, 80.96 to 67.73. The biggest single separator in this matchup is CharXiv, where the scores are 81.4% and 91.3%.
Which is better for multimodal and grounded tasks, Gemini 3 Pro or Kimi K3?
Gemini 3 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 81.1 versus 78.5. Inside this category, CharXiv is the benchmark that creates the most daylight between them.
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