Model comparison
Gemini 2.5 Pro vs Kimi K3
Head-to-head evidence from 17 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 2.5 Pro #70 (Supported); Kimi K3 #4 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 2.5 Pro and Kimi K3 share 17 comparable benchmark results. 1 of 8 categories are comparable. 7 results are unique to Gemini 2.5 Pro; 40 to Kimi K3.
Updated July 23, 2026- Shared results
- 17
- Gemini 2.5 Pro only
- 7
- Kimi K3 only
- 40
- Comparable categories
- 1 / 8
Pick Kimi K3 if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 17 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 57.25. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K3's sharpest advantage is in knowledge, where it averages 61 against 27.4. The single biggest benchmark swing on the page is HLE, 18.8% to 56%.
Kimi K3 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $1.25 input / $10.00 output per 1M tokens for Gemini 2.5 Pro. Kimi K3 is the reasoning model in the pair, while Gemini 2.5 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. Kimi K3 gives you the larger context window at 1.05M, compared with 1M for Gemini 2.5 Pro.
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 2.5 Pro | Δ | Kimi K3 |
|---|---|---|---|
| Knowledge | Gemini 2.5 Pro27.4 | Margin→ 33.6 | Kimi K361.0 |
| Agentic | Gemini 2.5 ProNot measured | MarginNo overlap | Kimi K389.5 |
| Coding | Gemini 2.5 Pro63.8 | MarginNo overlap | Kimi K3Not measured |
| Math | Gemini 2.5 Pro11.6 | MarginNo overlap | Kimi K3Not measured |
| Multimodal | Gemini 2.5 ProNot measured | MarginNo overlap | Kimi K378.5 |
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 2.5 Pro | Kimi K3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 2.5 Pro$1.25 input / $10 output | Kimi K3$3 input / $15 output | Gemini 2.5 Pro has the lower combined listed price. |
| Generation speedtokens per second | Gemini 2.5 Pro117 tok/s | Kimi K3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 2.5 Pro21.19 s | Kimi K3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 2.5 Pro1M | Kimi K31.05M | Kimi K3 lists the larger context window. |
Benchmark Deep Dive
Agentic23 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K3 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 7.1% | 50.1% | Kimi K3 leads |
| τ²-bench resultsSource | 54.1% | — | Not comparable |
| Gert LabsSource | 42.01% | — | Not comparable |
| GDPval-AASource | 8.3% | 59.0% | Kimi K3 leads |
| GDPval-AASource | 665 | 1679 | 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 |
| JobBenchSource | — | 52.9% | Not comparable |
| APEX-AgentsSource | — | 37.6% | Not comparable |
| SpreadsheetBench 2Source | — | 34.8% | Not comparable |
| DECK-BenchSource | — | 73.5% | 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 2.5 Pro | Kimi K3 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 63.8% | — | Not comparable |
| Vibe Code BenchSource | 0.40% | — | Not comparable |
| AA Coding IndexSource | 33.3% | 76.2% | Kimi K3 leads |
| AA-SciCodeSource | 42.8% | 58.7% | Kimi K3 leads |
| 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 |
Reasoning2 benchmarks
KnowledgeKimi K3 wins10 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K3 | Result |
|---|---|---|---|
| GPQASource | 83% | 93.5% | Kimi K3 leads |
| HLESource | 18.8% | 56% | Kimi K3 leads |
| Artificial Analysis Intelligence IndexSource | 25.8% | 57.1% | Kimi K3 leads |
| AA-GPQA DiamondSource | 84.4% | 93.5% | Kimi K3 leads |
| AA-HLESource | 21.1% | 44.3% | Kimi K3 leads |
| AA-Omniscience IndexSource | -14.3% | 18.4% | Kimi K3 leads |
| AA-Omniscience AccuracySource | 39.0% | 46.0% | Kimi K3 leads |
| AA-Omniscience Hallucination RateSource | 87.4% | 50.9% | Kimi K3 leads |
| GPQA-DSource | — | 93.5% | Not comparable |
| HLE w/o toolsSource | — | 43.5% | Not comparable |
Math2 benchmarks
Multimodal15 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K3 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 74.9% | 80.5% | Kimi K3 leads |
| Design Arena WebsiteSource | 1197 | 1386 | Kimi K3 leads |
| OfficeQA ProSource | — | 63.3% | Not comparable |
| MMMU-ProSource | — | 81.6% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 83.4% | Not comparable |
| CharXiv w/o toolsSource | — | 84.8% | Not comparable |
| CharXivSource | — | 91.3% | Not comparable |
| MathVisionSource | — | 94.3% | 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 |
Inst. Following1 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K3 | Result |
|---|---|---|---|
| AA-IFBenchSource | 48.7% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, Gemini 2.5 Pro or Kimi K3?
Kimi K3 is ahead on BenchLM's BenchAlign leaderboard, 80.96 to 57.25. The biggest single separator in this matchup is HLE, where the scores are 18.8% and 56%.
Which is better for knowledge tasks, Gemini 2.5 Pro or Kimi K3?
Kimi K3 has the edge for knowledge tasks in this comparison, averaging 61 versus 27.4. Inside this category, HLE is the benchmark that creates the most daylight between them.
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