Model comparison
Gemini 2.5 Flash vs Kimi K2.6
Head-to-head evidence from 16 shared benchmark results across 7 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Gemini 2.5 Flash unranked; Kimi K2.6 #13
Evidence parity. Gemini 2.5 Flash and Kimi K2.6 share 16 comparable benchmark results. 1 of 8 categories are comparable. 0 results are unique to Gemini 2.5 Flash; 44 to Kimi K2.6.
Updated July 13, 2026- Shared results
- 16
- Gemini 2.5 Flash only
- 0
- Kimi K2.6 only
- 44
- Comparable categories
- 1 / 8
Pick Kimi K2.6 if you want the stronger benchmark profile. Gemini 2.5 Flash only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 7 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 K2.6 is clearly ahead on the provisional aggregate, 74 to 38. 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 4.7. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 4.844% to 38.966%.
Kimi K2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $0.30 input / $2.50 output per 1M tokens for Gemini 2.5 Flash. Kimi K2.6 is the reasoning model in the pair, while Gemini 2.5 Flash 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 Flash 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 Flash | Δ | Kimi K2.6 |
|---|---|---|---|
| Math | Gemini 2.5 Flash4.7 | Margin→ 62.4 | Kimi K2.667.1 |
| Agentic | Gemini 2.5 FlashNot measured | MarginNo overlap | Kimi K2.673.5 |
| Coding | Gemini 2.5 FlashNot measured | MarginNo overlap | Kimi K2.672.6 |
| Knowledge | Gemini 2.5 FlashNot measured | MarginNo overlap | Kimi K2.642.2 |
| Multimodal | Gemini 2.5 FlashNot 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 4.844%B 38.966%Winner: Kimi K2.6Δ 34.1FrontierMath v2 (Tiers 1-3): Gemini 2.5 Flash scored 4.844%; Kimi K2.6 scored 38.966%. 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 Flash scored 4.167%; Kimi K2.6 scored 14.580%. 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 Flash | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 2.5 Flash$0.3 input / $2.5 output | Kimi K2.6$0.95 input / $4 output | Gemini 2.5 Flash has the lower combined listed price. |
| Generation speedtokens per second | Gemini 2.5 Flash221 tok/s | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 2.5 Flash0.50 s | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 2.5 Flash1M | Kimi K2.6256K | Gemini 2.5 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | Gemini 2.5 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| Tau2-TelecomSource | 14.9% | 95.9% | 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 |
| AA Agentic IndexSource | — | 30.3% | Not comparable |
| GDPval-AASource | — | 34.5% | Not comparable |
| GDPval-AASource | — | 1190 | Not comparable |
| APEX-Agents-AASource | — | 28.5% | Not comparable |
| Gert LabsSource | — | 56.82% | 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 |
Coding13 benchmarks
| Benchmark | Gemini 2.5 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| Terminal-Bench HardSource | 12.1% | 43.9% | Kimi K2.6 leads |
| AA-SciCodeSource | 29.1% | 53.5% | Kimi K2.6 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 |
| Vibe Code BenchSource | — | 37.89% | Not comparable |
| cursorBench31Source | — | 47.6% | Not comparable |
| AA Coding IndexSource | — | 61.8% | Not comparable |
| AA Terminal-Bench 2.1Source | — | 65.9% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Gemini 2.5 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.1% | 44.2% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 68.3% | 91.1% | Kimi K2.6 leads |
| AA-HLESource | 5.1% | 35.9% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | -42.0% | 6.4% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 26.5% | 32.8% | Kimi K2.6 leads |
| AA-Omniscience Hallucination RateSource | 93.3% | 39.3% | Kimi K2.6 leads |
| GPQASource | — | 90.5% | Not comparable |
| GPQA-DSource | — | 90.5% | Not comparable |
| HLESource | — | 34.7% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
MathKimi K2.6 wins5 benchmarks
Multimodal7 benchmarks
| Benchmark | Gemini 2.5 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 65.5% | 79.4% | Kimi K2.6 leads |
| Design Arena WebsiteSource | 1158 | 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 Flash | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | 39.0% | 76.0% | Kimi K2.6 leads |
Frequently Asked Questions (2)
Which is better, Gemini 2.5 Flash or Kimi K2.6?
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 74 to 38. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 4.844% and 38.966%.
Which is better for math, Gemini 2.5 Flash or Kimi K2.6?
Kimi K2.6 has the edge for math in this comparison, averaging 67.1 versus 4.7. 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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