Model comparison
Gemini 2.5 Pro vs Kimi K2.6
Head-to-head evidence from 25 shared benchmark results across 7 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Gemini 2.5 Pro unranked; Kimi K2.6 #13
Evidence parity. Gemini 2.5 Pro and Kimi K2.6 share 25 comparable benchmark results. 3 of 8 categories are comparable. 0 results are unique to Gemini 2.5 Pro; 35 to Kimi K2.6.
Updated July 13, 2026- Shared results
- 25
- Gemini 2.5 Pro only
- 0
- Kimi K2.6 only
- 35
- Comparable categories
- 3 / 8
Pick Kimi K2.6 if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 25 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 K2.6 is clearly ahead on the provisional aggregate, 74 to 60. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.6's sharpest advantage is in mathematics, where it averages 67.1 against 11.6. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 14.138% to 38.966%.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $10.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.6. That is roughly 2.5x on output cost alone. Kimi K2.6 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. Gemini 2.5 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 2.5 Pro | Δ | Kimi K2.6 |
|---|---|---|---|
| Math | Gemini 2.5 Pro11.6 | Margin→ 55.5 | Kimi K2.667.1 |
| Knowledge | Gemini 2.5 Pro27.5 | Margin→ 14.7 | Kimi K2.642.2 |
| Coding | Gemini 2.5 Pro63.8 | Margin→ 8.8 | Kimi K2.672.6 |
| Agentic | Gemini 2.5 ProNot measured | MarginNo overlap | Kimi K2.673.5 |
| Multimodal | Gemini 2.5 ProNot measured | MarginNo overlap | Kimi K2.679.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 14.138%B 38.966%Winner: Kimi K2.6Δ 24.8FrontierMath v2 (Tiers 1-3): Gemini 2.5 Pro scored 14.138%; Kimi K2.6 scored 38.966%. Kimi K2.6 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 63.8%B 80.2%Winner: Kimi K2.6Δ 16.4SWE-bench Verified: Gemini 2.5 Pro scored 63.8%; Kimi K2.6 scored 80.2%. Kimi K2.6 wins this benchmark. - Source ↗
HLE
KnowledgeA 18.8%B 34.7%Winner: Kimi K2.6Δ 15.9HLE: Gemini 2.5 Pro scored 18.8%; Kimi K2.6 scored 34.7%. Kimi K2.6 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 4.167%B 14.580%Winner: Kimi K2.6Δ 10.4FrontierMath v2 (Tier 4): Gemini 2.5 Pro scored 4.167%; Kimi K2.6 scored 14.580%. Kimi K2.6 wins this benchmark. - Source ↗
GPQA
KnowledgeA 83%B 90.5%Winner: Kimi K2.6Δ 7.5GPQA: Gemini 2.5 Pro scored 83%; Kimi K2.6 scored 90.5%. 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 2.5 Pro | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 2.5 Pro$1.25 input / $10 output | Kimi K2.6$0.95 input / $4 output | Kimi K2.6 has the lower combined listed price. |
| Generation speedtokens per second | Gemini 2.5 Pro117 tok/s | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 2.5 Pro21.19 s | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 2.5 Pro1M | Kimi K2.6256K | Gemini 2.5 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 7.1% | 30.3% | Kimi K2.6 leads |
| Tau2-TelecomSource | 54.1% | 95.9% | Kimi K2.6 leads |
| Gert LabsSource | 42.01% | 56.82% | Kimi K2.6 leads |
| GDPval-AASource | 8.0% | 34.5% | Kimi K2.6 leads |
| GDPval-AASource | 661 | 1190 | 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 |
| Claw-EvalSource | — | 62.3% | Not comparable |
| DeepSearchQASource | — | 92.5% | Not comparable |
| WideResearchSource | — | 80.8% | Not comparable |
| APEX-Agents-AASource | — | 28.5% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
| OSWorld 2.0Source | — | 4.6% | Not comparable |
| AA BriefcaseSource | — | 809 | Not comparable |
| AA AutomationBenchSource | — | 19.6% | Not comparable |
| AA EnterpriseOps-GymSource | — | 38.5% | Not comparable |
| AA Harvey LABSource | — | 0.0% | Not comparable |
| AA ITBenchSource | — | 31.2% | Not comparable |
| AA Tau3 BankingSource | — | 20.6% | Not comparable |
CodingKimi K2.6 wins13 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 63.8% | 80.2% | Kimi K2.6 leads |
| Vibe Code BenchSource | 0.40% | 37.89% | Kimi K2.6 leads |
| AA Coding IndexSource | 33.3% | 61.8% | Kimi K2.6 leads |
| Terminal-Bench HardSource | 26.5% | 43.9% | Kimi K2.6 leads |
| AA-SciCodeSource | 42.8% | 53.5% | Kimi K2.6 leads |
| 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 |
| AA Terminal-Bench 2.1Source | — | 65.9% | Not comparable |
Reasoning2 benchmarks
KnowledgeKimi K2.6 wins10 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| GPQASource | 83% | 90.5% | Kimi K2.6 leads |
| HLESource | 18.8% | 34.7% | Kimi K2.6 leads |
| Artificial Analysis Intelligence IndexSource | 25.8% | 44.2% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 84.4% | 91.1% | Kimi K2.6 leads |
| AA-HLESource | 21.1% | 35.9% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | -14.3% | 6.4% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 39.0% | 32.8% | Gemini 2.5 Pro leads |
| AA-Omniscience Hallucination RateSource | 87.4% | 39.3% | Kimi K2.6 leads |
| GPQA-DSource | — | 90.5% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
MathKimi K2.6 wins5 benchmarks
Multimodal7 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 74.9% | 79.4% | Kimi K2.6 leads |
| Design Arena WebsiteSource | 1210 | 1318 | Kimi K2.6 leads |
| MMMU-ProSource | — | 79.4% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 80.1% | Not comparable |
| CharXivSource | — | 80.4% | Not comparable |
| MathVisionSource | — | 87.4% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Gemini 2.5 Pro | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | 48.7% | 76.0% | Kimi K2.6 leads |
Frequently Asked Questions (4)
Which is better, Gemini 2.5 Pro or Kimi K2.6?
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 74 to 60. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 14.138% and 38.966%.
Which is better for knowledge tasks, Gemini 2.5 Pro or Kimi K2.6?
Kimi K2.6 has the edge for knowledge tasks in this comparison, averaging 42.2 versus 27.5. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, Gemini 2.5 Pro or Kimi K2.6?
Kimi K2.6 has the edge for coding in this comparison, averaging 72.6 versus 63.8. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.
Which is better for math, Gemini 2.5 Pro or Kimi K2.6?
Kimi K2.6 has the edge for math in this comparison, averaging 67.1 versus 11.6. Inside this category, FrontierMath v2 (Tiers 1-3) 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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