Model comparison
Kimi K2.5 vs Ling 2.6 Flash
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: Kimi K2.5 #54 (Supported); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 and Ling 2.6 Flash share 17 comparable benchmark results. 3 of 8 categories are comparable. 46 results are unique to Kimi K2.5; 1 to Ling 2.6 Flash.
Updated July 21, 2026- Shared results
- 17
- Kimi K2.5 only
- 46
- Ling 2.6 Flash only
- 1
- Comparable categories
- 3 / 8
Pick Kimi K2.5 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 5 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 K2.5 is clearly ahead on the BenchAlign aggregate, 59.66 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5's sharpest advantage is in instruction following, where it averages 93.9 against 57. The single biggest benchmark swing on the page is GPQA, 87.6% to 59%. Ling 2.6 Flash does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Ling 2.6 Flash gives you the larger context window at 262K, 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 | Kimi K2.5 | Δ | Ling 2.6 Flash |
|---|---|---|---|
| Inst. Following | Kimi K2.593.9 | Margin← 36.9 | Ling 2.6 Flash57.0 |
| Coding | Kimi K2.559.4 | Margin← 32.4 | Ling 2.6 Flash27.0 |
| Knowledge | Kimi K2.556.9 | Margin→ 2.1 | Ling 2.6 Flash59.0 |
| Agentic | Kimi K2.555.0 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Reasoning | Kimi K2.561.0 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Math | Kimi K2.560.6 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Multilingual | Kimi K2.582.3 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Multimodal | Kimi K2.578.5 | MarginNo overlap | Ling 2.6 FlashNot measured |
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 | Kimi K2.5 | Ling 2.6 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5$0.6 input / $3 output | Ling 2.6 FlashNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Kimi K2.545 tok/s | Ling 2.6 Flash209.5 tok/s | Ling 2.6 Flash has the higher measured throughput. |
| First-answer latencyseconds to first token | Kimi K2.52.38 s | Ling 2.6 Flash1.07 s | Ling 2.6 Flash reaches the first token sooner. |
| Context windowmaximum listed tokens | Kimi K2.5256K | Ling 2.6 Flash262K | Ling 2.6 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic19 benchmarks
| Benchmark | Kimi K2.5 | Ling 2.6 Flash | Result |
|---|---|---|---|
| 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% | 86% | Kimi K2.5 leads |
| APEX-Agents-AASource | 11.5% | — | Not comparable |
| Gert LabsSource | 45.88% | — | Not comparable |
| ResearchClawBenchSource | 14.0% | — | Not comparable |
| JobBenchSource | 8.7% | — | Not comparable |
| AA Agentic IndexSource | 21.7% | 2.3% | Kimi K2.5 leads |
| GDPval-AASource | 25.4% | 2.2% | Kimi K2.5 leads |
| GDPval-AASource | 1009 | 545 | Kimi K2.5 leads |
CodingKimi K2.5 wins10 benchmarks
| Benchmark | Kimi K2.5 | Ling 2.6 Flash | Result |
|---|---|---|---|
| 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% | 27% | Kimi K2.5 leads |
| AA-SciCodeSource | 49.0% | 27.1% | Kimi K2.5 leads |
| AA Coding IndexSource | 46.8% | 25.3% | Kimi K2.5 leads |
Reasoning3 benchmarks
KnowledgeLing 2.6 Flash wins12 benchmarks
| Benchmark | Kimi K2.5 | Ling 2.6 Flash | Result |
|---|---|---|---|
| GPQASource | 87.6% | 59% | Kimi K2.5 leads |
| 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 |
| Artificial Analysis Intelligence IndexSource | 35.4% | 14.1% | Kimi K2.5 leads |
| AA-GPQA DiamondSource | 87.9% | 59.3% | Kimi K2.5 leads |
| AA-HLESource | 29.4% | 6.2% | Kimi K2.5 leads |
| AA-Omniscience IndexSource | -8.1% | -65.7% | Kimi K2.5 leads |
| AA-Omniscience AccuracySource | 34.3% | 15.4% | Kimi K2.5 leads |
| AA-Omniscience Hallucination RateSource | 64.6% | 95.8% | Kimi K2.5 leads |
Math9 benchmarks
| Benchmark | Kimi K2.5 | Ling 2.6 Flash | 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 (4)
Which is better, Kimi K2.5 or Ling 2.6 Flash?
Kimi K2.5 is ahead on BenchLM's BenchAlign leaderboard, 59.66 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 87.6% and 59%.
Which is better for knowledge tasks, Kimi K2.5 or Ling 2.6 Flash?
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 56.9. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, Kimi K2.5 or Ling 2.6 Flash?
Kimi K2.5 has the edge for coding in this comparison, averaging 59.4 versus 27. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for instruction following, Kimi K2.5 or Ling 2.6 Flash?
Kimi K2.5 has the edge for instruction following in this comparison, averaging 93.9 versus 57. Inside this category, AA-IFBench 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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