Model comparison
Gemini 3.6 Flash vs Kimi K2.5
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 3.6 Flash unranked (Not scored); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.6 Flash and Kimi K2.5 share 14 comparable benchmark results. 1 of 8 categories are comparable. 5 results are unique to Gemini 3.6 Flash; 49 to Kimi K2.5.
Updated July 21, 2026- Shared results
- 14
- Gemini 3.6 Flash only
- 5
- Kimi K2.5 only
- 49
- Comparable categories
- 1 / 8
Treat this as a split decision. Gemini 3.6 Flash makes more sense if agentic is the priority or you need the larger 1M context window; Kimi K2.5 is the better fit 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 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
Gemini 3.6 Flash and Kimi K2.5 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Gemini 3.6 Flash is also the more expensive model on tokens at $1.50 input / $7.50 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 2.5x on output cost alone. Gemini 3.6 Flash is the reasoning model in the pair, while Kimi K2.5 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 3.6 Flash gives you the larger context window at 1M, compared with 256K for Kimi K2.5.
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 3.6 Flash | Δ | Kimi K2.5 |
|---|---|---|---|
| Agentic | Gemini 3.6 Flash83.0 | Margin← 28.0 | Kimi K2.555.0 |
| Coding | Gemini 3.6 FlashNot measured | MarginNo overlap | Kimi K2.559.4 |
| Reasoning | Gemini 3.6 FlashNot measured | MarginNo overlap | Kimi K2.561.0 |
| Knowledge | Gemini 3.6 FlashNot measured | MarginNo overlap | Kimi K2.556.9 |
| Math | Gemini 3.6 FlashNot measured | MarginNo overlap | Kimi K2.560.6 |
| Multilingual | Gemini 3.6 FlashNot measured | MarginNo overlap | Kimi K2.582.3 |
| Multimodal | Gemini 3.6 FlashNot measured | MarginNo overlap | Kimi K2.578.5 |
| Inst. Following | Gemini 3.6 FlashNot measured | MarginNo overlap | Kimi K2.593.9 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.6 Flash | Kimi K2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.6 Flash$1.5 input / $7.5 output | Kimi K2.5$0.6 input / $3 output | Kimi K2.5 has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.6 FlashNot available | Kimi K2.545 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.6 FlashNot available | Kimi K2.52.38 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.6 Flash1M | Kimi K2.5256K | Gemini 3.6 Flash lists the larger context window. |
Benchmark Deep Dive
AgenticGemini 3.6 Flash wins23 benchmarks
| Benchmark | Gemini 3.6 Flash | Kimi K2.5 | Result |
|---|---|---|---|
| OSWorld-VerifiedSource | 83% | — | Not comparable |
| GDPval-AASource | 1421 | 1009 | Gemini 3.6 Flash leads |
| AA Agentic IndexSource | 38.7% | 21.7% | Gemini 3.6 Flash leads |
| GDPval-AASource | 46.1% | 25.4% | Gemini 3.6 Flash leads |
| AA BriefcaseSource | 961 | — | Not comparable |
| AA Tau3 BankingSource | 24.5% | — | Not comparable |
| aaTerminalBench21Source | 77.5% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 50.8% | Not comparable |
| BrowseCompSource | — | 60.6% | Not comparable |
| Claw-EvalSource | — | 52.3% | Not comparable |
| QwenClawBenchSource | — | 54.3% | Not comparable |
| τ³-bench resultsSource | — | 65.7% | Not comparable |
| DeepSearchQASource | — | 77.1% | Not comparable |
| DeepPlanningSource | — | 14.4% | Not comparable |
| ToolathlonSource | — | 27.8% | Not comparable |
| MCP AtlasSource | — | 29.5% | Not comparable |
| MCP-TasksSource | — | 59.1% | Not comparable |
| WideResearchSource | — | 72.7% | Not comparable |
| τ²-bench resultsSource | — | 95.9% | Not comparable |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
| Gert LabsSource | — | 45.88% | Not comparable |
| ResearchClawBenchSource | — | 14.0% | Not comparable |
| JobBenchSource | — | 8.7% | Not comparable |
Coding11 benchmarks
| Benchmark | Gemini 3.6 Flash | Kimi K2.5 | Result |
|---|---|---|---|
| deepSweSource | 49% | — | Not comparable |
| AA Coding IndexSource | 69.2% | 46.8% | Gemini 3.6 Flash leads |
| AA-SciCodeSource | 52.7% | 49.0% | Gemini 3.6 Flash leads |
| SWE-bench VerifiedSource | — | 76.8% | Not comparable |
| SWE-bench Verified*Source | — | 70.8% | Not comparable |
| LiveCodeBench v6Source | — | 85.0% | Not comparable |
| SWE-bench ProSource | — | 50.7% | Not comparable |
| SWE MultilingualSource | — | 73% | Not comparable |
| SWE-RebenchSource | — | 58.5% | Not comparable |
| React Native EvalsSource | — | 77.2% | Not comparable |
| SciCodeSource | — | 48.7% | Not comparable |
Reasoning3 benchmarks
Knowledge12 benchmarks
| Benchmark | Gemini 3.6 Flash | Kimi K2.5 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 50.1% | 35.4% | Gemini 3.6 Flash leads |
| AA-GPQA DiamondSource | 92.8% | 87.9% | Gemini 3.6 Flash leads |
| AA-HLESource | 38.3% | 29.4% | Gemini 3.6 Flash leads |
| AA-Omniscience IndexSource | 23.5% | -8.1% | Gemini 3.6 Flash leads |
| AA-Omniscience AccuracySource | 50.2% | 34.3% | Gemini 3.6 Flash leads |
| AA-Omniscience Hallucination RateSource | 53.5% | 64.6% | Gemini 3.6 Flash leads |
| GPQASource | — | 87.6% | Not comparable |
| GPQA-DSource | — | 87.6% | Not comparable |
| SuperGPQASource | — | 69.2% | Not comparable |
| MMLU-ProSource | — | 87.1% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 87.1% | Not comparable |
| HLESource | — | 30.1% | Not comparable |
Math9 benchmarks
| Benchmark | Gemini 3.6 Flash | Kimi K2.5 | Result |
|---|---|---|---|
| AIME 2025Source | — | 96.1% | Not comparable |
| AIME26Source | — | 95.8% | Not comparable |
| AIME25 (Arcee)Source | — | 96.3% | Not comparable |
| HMMT Feb 2025Source | — | 95.4% | Not comparable |
| HMMT Nov 2025Source | — | 91.1% | Not comparable |
| HMMT Feb 2026Source | — | 87.1% | Not comparable |
| MMAnswerBenchSource | — | 81.8% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 27.900% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 4.200% | Not comparable |
Multilingual2 benchmarks
Multimodal6 benchmarks
Frequently Asked Questions (2)
Which is better, Gemini 3.6 Flash or Kimi K2.5?
Gemini 3.6 Flash and Kimi K2.5 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for agentic tasks, Gemini 3.6 Flash or Kimi K2.5?
Gemini 3.6 Flash has the edge for agentic tasks in this comparison, averaging 83 versus 55. Inside this category, GDPval-AA 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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