Model comparison
Kimi K2.5 vs Step 3.7 Flash
Head-to-head evidence from 26 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Kimi K2.5 #22; Step 3.7 Flash unranked
BenchAlign evidence: Kimi K2.5 supported; Step 3.7 Flash estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 and Step 3.7 Flash share 26 comparable benchmark results. 2 of 8 categories are comparable. 38 results are unique to Kimi K2.5; 4 to Step 3.7 Flash.
Updated July 16, 2026- Shared results
- 26
- Kimi K2.5 only
- 38
- Step 3.7 Flash only
- 4
- Comparable categories
- 2 / 8
Pick Kimi K2.5 if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 26 shared benchmark results across 6 evidence categories; 2 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 provisional aggregate, 61 to 57. 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 coding, where it averages 59.4 against 56.3. The single biggest benchmark swing on the page is BrowseComp, 60.6% to 75.8%. Step 3.7 Flash does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Kimi K2.5 is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. That is roughly 2.6x on output cost alone. Step 3.7 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.
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 | Step 3.7 Flash |
|---|---|---|---|
| Agentic | Kimi K2.555.0 | Margin→ 11.4 | Step 3.7 Flash66.4 |
| Coding | Kimi K2.559.4 | Margin← 3.1 | Step 3.7 Flash56.3 |
| Reasoning | Kimi K2.561.0 | MarginNo overlap | Step 3.7 FlashNot measured |
| Knowledge | Kimi K2.557.2 | MarginNo overlap | Step 3.7 FlashNot measured |
| Math | Kimi K2.560.6 | MarginNo overlap | Step 3.7 FlashNot measured |
| Multilingual | Kimi K2.582.3 | MarginNo overlap | Step 3.7 FlashNot measured |
| Multimodal | Kimi K2.578.5 | MarginNo overlap | Step 3.7 FlashNot measured |
| Inst. Following | Kimi K2.593.9 | MarginNo overlap | Step 3.7 FlashNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 60.6%B 75.8%Winner: Step 3.7 FlashΔ 15.2BrowseComp: Kimi K2.5 scored 60.6%; Step 3.7 Flash scored 75.8%. Step 3.7 Flash wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 50.8%B 59.5%Winner: Step 3.7 FlashΔ 8.7Terminal-Bench 2.0: Kimi K2.5 scored 50.8%; Step 3.7 Flash scored 59.5%. Step 3.7 Flash wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 50.7%B 56.3%Winner: Step 3.7 FlashΔ 5.6SWE-bench Pro: Kimi K2.5 scored 50.7%; Step 3.7 Flash scored 56.3%. Step 3.7 Flash wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.5 | Step 3.7 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5$0.6 input / $3 output | Step 3.7 Flash$0.2 input / $1.15 output | Step 3.7 Flash has the lower combined listed price. |
| Generation speedtokens per second | Kimi K2.545 tok/s | Step 3.7 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.52.38 s | Step 3.7 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.5256K | Step 3.7 Flash256K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticStep 3.7 Flash wins20 benchmarks
| Benchmark | Kimi K2.5 | Step 3.7 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50.8% | 59.5% | Step 3.7 Flash leads |
| BrowseCompSource | 60.6% | 75.8% | Step 3.7 Flash leads |
| Claw-EvalSource | 52.3% | 67.1% | Step 3.7 Flash leads |
| QwenClawBenchSource | 54.3% | — | Not comparable |
| τ³-bench resultsSource | 65.7% | — | Not comparable |
| DeepSearchQASource | 77.1% | 92.8% | Step 3.7 Flash leads |
| DeepPlanningSource | 14.4% | — | Not comparable |
| ToolathlonSource | 27.8% | 49.5% | Step 3.7 Flash leads |
| MCP AtlasSource | 29.5% | — | Not comparable |
| MCP-TasksSource | 59.1% | — | Not comparable |
| WideResearchSource | 72.7% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | 98.5% | Step 3.7 Flash leads |
| APEX-Agents-AASource | 11.5% | 14.8% | Step 3.7 Flash leads |
| Gert LabsSource | 45.88% | 51.57% | Step 3.7 Flash leads |
| ResearchClawBenchSource | 14.0% | — | Not comparable |
| JobBenchSource | 8.7% | — | Not comparable |
| AA Agentic IndexSource | 21.7% | 21.5% | Kimi K2.5 leads |
| GDPval-AASource | 25.4% | 25.9% | Step 3.7 Flash leads |
| GDPval-AASource | 1009 | 1017 | Step 3.7 Flash leads |
| HLE w/ toolsSource | — | 47.2% | Not comparable |
CodingKimi K2.5 wins12 benchmarks
| Benchmark | Kimi K2.5 | Step 3.7 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% | 56.3% | Step 3.7 Flash leads |
| SWE MultilingualSource | 73% | — | Not comparable |
| SWE-RebenchSource | 58.5% | — | Not comparable |
| React Native EvalsSource | 77.2% | — | Not comparable |
| SciCodeSource | 48.7% | — | Not comparable |
| Terminal-Bench HardSource | 34.8% | 35.6% | Step 3.7 Flash leads |
| AA-SciCodeSource | 49.0% | 40.0% | Kimi K2.5 leads |
| AA Coding IndexSource | 46.8% | 39.6% | Kimi K2.5 leads |
| Terminal-Bench 2.0Source | — | 59.5% | Not comparable |
Reasoning3 benchmarks
Knowledge12 benchmarks
| Benchmark | Kimi K2.5 | Step 3.7 Flash | Result |
|---|---|---|---|
| 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 |
| Artificial Analysis Intelligence IndexSource | 35.4% | 30.3% | Kimi K2.5 leads |
| AA-GPQA DiamondSource | 87.9% | 80.9% | Kimi K2.5 leads |
| AA-HLESource | 29.4% | 19.9% | Kimi K2.5 leads |
| AA-Omniscience IndexSource | -8.1% | -37.5% | Kimi K2.5 leads |
| AA-Omniscience AccuracySource | 34.3% | 25.4% | Kimi K2.5 leads |
| AA-Omniscience Hallucination RateSource | 64.6% | 84.4% | Kimi K2.5 leads |
Math9 benchmarks
| Benchmark | Kimi K2.5 | Step 3.7 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
Multimodal8 benchmarks
| Benchmark | Kimi K2.5 | Step 3.7 Flash | Result |
|---|---|---|---|
| MMMU-ProSource | 78.5% | — | Not comparable |
| Video-MMESource | 87.4% | — | Not comparable |
| MMVUSource | 80.4% | — | Not comparable |
| VideoMMMUSource | 86.6% | — | Not comparable |
| AA-MMMU-ProSource | 75.4% | 75.3% | Kimi K2.5 leads |
| Design Arena WebsiteSource | 1284 | 1218 | Kimi K2.5 leads |
| SimpleVQASource | — | 79.2% | Not comparable |
| V*Source | — | 95.3% | Not comparable |
Frequently Asked Questions (3)
Which is better, Kimi K2.5 or Step 3.7 Flash?
Kimi K2.5 is ahead on BenchLM's provisional leaderboard, 61 to 57. The biggest single separator in this matchup is BrowseComp, where the scores are 60.6% and 75.8%.
Which is better for coding, Kimi K2.5 or Step 3.7 Flash?
Kimi K2.5 has the edge for coding in this comparison, averaging 59.4 versus 56.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Kimi K2.5 or Step 3.7 Flash?
Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 66.4 versus 55. Inside this category, Toolathlon 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.
Related Comparisons
The AI models change fast. We track them for you.
A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.