Model comparison
Gemini 3.1 Flash-Lite vs Kimi K2.6
Head-to-head evidence from 21 shared benchmark results across 6 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: Gemini 3.1 Flash-Lite unranked; Kimi K2.6 #13
Evidence parity. Gemini 3.1 Flash-Lite and Kimi K2.6 share 21 comparable benchmark results. 1 of 8 categories are comparable. 0 results are unique to Gemini 3.1 Flash-Lite; 39 to Kimi K2.6.
Updated July 13, 2026- Shared results
- 21
- Gemini 3.1 Flash-Lite only
- 0
- Kimi K2.6 only
- 39
- Comparable categories
- 1 / 8
Pick Kimi K2.6 if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite 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 21 shared benchmark results across 6 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 46. 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 multimodal & grounded, where it averages 79.8 against 73.2. The single biggest benchmark swing on the page is CharXiv, 73.2% to 80.4%.
Kimi K2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $0.25 input / $1.50 output per 1M tokens for Gemini 3.1 Flash-Lite. That is roughly 2.7x on output cost alone. Kimi K2.6 is the reasoning model in the pair, while Gemini 3.1 Flash-Lite 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 3.1 Flash-Lite 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 3.1 Flash-Lite | Δ | Kimi K2.6 |
|---|---|---|---|
| Multimodal | Gemini 3.1 Flash-Lite73.2 | Margin→ 6.6 | Kimi K2.679.8 |
| Agentic | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Kimi K2.673.5 |
| Coding | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Kimi K2.672.6 |
| Knowledge | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Kimi K2.642.2 |
| Math | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Kimi K2.667.1 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
CharXiv
MultimodalA 73.2%B 80.4%Winner: Kimi K2.6Δ 7.2CharXiv: Gemini 3.1 Flash-Lite scored 73.2%; Kimi K2.6 scored 80.4%. 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 3.1 Flash-Lite | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Flash-Lite$0.25 input / $1.5 output | Kimi K2.6$0.95 input / $4 output | Gemini 3.1 Flash-Lite has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Flash-Lite205 tok/s | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.1 Flash-Lite7.50 s | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.1 Flash-Lite1M | Kimi K2.6256K | Gemini 3.1 Flash-Lite lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Kimi K2.6 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 6.2% | 30.3% | Kimi K2.6 leads |
| APEX-Agents-AASource | 12.2% | 28.5% | Kimi K2.6 leads |
| Tau2-TelecomSource | 31.3% | 95.9% | Kimi K2.6 leads |
| GDPval-AASource | 6.9% | 34.5% | Kimi K2.6 leads |
| GDPval-AASource | 639 | 1190 | Kimi K2.6 leads |
| Gert LabsSource | 38.46% | 56.82% | 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 |
| 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 3.1 Flash-Lite | Kimi K2.6 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 0.00% | 37.89% | Kimi K2.6 leads |
| AA Coding IndexSource | 34.7% | 61.8% | Kimi K2.6 leads |
| Terminal-Bench HardSource | 24.2% | 43.9% | Kimi K2.6 leads |
| AA-SciCodeSource | 41.9% | 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 |
| cursorBench31Source | — | 47.6% | Not comparable |
| AA Terminal-Bench 2.1Source | — | 65.9% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Kimi K2.6 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.0% | 44.2% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 82.2% | 91.1% | Kimi K2.6 leads |
| AA-HLESource | 16.2% | 35.9% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | -15.5% | 6.4% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 36.4% | 32.8% | Gemini 3.1 Flash-Lite leads |
| AA-Omniscience Hallucination RateSource | 81.6% | 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 |
Math5 benchmarks
MultimodalKimi K2.6 wins7 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Kimi K2.6 | Result |
|---|---|---|---|
| CharXivSource | 73.2% | 80.4% | Kimi K2.6 leads |
| AA-MMMU-ProSource | 75.5% | 79.4% | Kimi K2.6 leads |
| MMMU-ProSource | — | 79.4% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 80.1% | Not comparable |
| MathVisionSource | — | 87.4% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| Design Arena WebsiteSource | — | 1318 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.2% | 76.0% | Gemini 3.1 Flash-Lite leads |
Frequently Asked Questions (2)
Which is better, Gemini 3.1 Flash-Lite or Kimi K2.6?
Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 74 to 46. The biggest single separator in this matchup is CharXiv, where the scores are 73.2% and 80.4%.
Which is better for multimodal and grounded tasks, Gemini 3.1 Flash-Lite or Kimi K2.6?
Kimi K2.6 has the edge for multimodal and grounded tasks in this comparison, averaging 79.8 versus 73.2. Inside this category, CharXiv 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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