Model comparison
Kimi K2.5 vs Kimi K2.5 (Reasoning)
Head-to-head evidence from 26 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Sibling matchup inside the Kimi K2.5 family.
Public leaderboard positions: Kimi K2.5 #54 (Supported); Kimi K2.5 (Reasoning) #57 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 and Kimi K2.5 (Reasoning) share 26 comparable benchmark results. 4 of 8 categories are comparable. 37 results are unique to Kimi K2.5; 1 to Kimi K2.5 (Reasoning).
Updated July 22, 2026- Shared results
- 26
- Kimi K2.5 only
- 37
- Kimi K2.5 (Reasoning) only
- 1
- Comparable categories
- 4 / 8
Kimi K2.5 makes more sense if you need the larger 256K context window or you would rather avoid the extra latency and token burn of a reasoning model, while Kimi K2.5 (Reasoning) is the cleaner fit if knowledge is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 26 shared benchmark results across 7 evidence categories; 4 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 and Kimi K2.5 (Reasoning) sit in the same Kimi K2.5 family. This page is less about two unrelated model lineages and more about how the siblings trade off on benchmark shape, token costs, and practical limits like context window.
Kimi K2.5 has the cleaner BenchAlign overall profile here, landing at 59.66 versus 59.35. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Kimi K2.5 (Reasoning) 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. Kimi K2.5 gives you the larger context window at 256K, compared with 128K for Kimi K2.5 (Reasoning).
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 | Kimi K2.5 (Reasoning) |
|---|---|---|---|
| Knowledge | Kimi K2.556.9 | Margin→ 30.3 | Kimi K2.5 (Reasoning)87.2 |
| Coding | Kimi K2.559.4 | Margin→ 17.4 | Kimi K2.5 (Reasoning)76.8 |
| Agentic | Kimi K2.555.0 | MarginTie | Kimi K2.5 (Reasoning)55.0 |
| Multimodal | Kimi K2.578.5 | MarginTie | Kimi K2.5 (Reasoning)78.5 |
| Reasoning | Kimi K2.561.0 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Math | Kimi K2.560.6 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Multilingual | Kimi K2.582.3 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Inst. Following | Kimi K2.593.9 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.5 | Kimi K2.5 (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5$0.6 input / $3 output | Kimi K2.5 (Reasoning)$0.6 input / $3 output | Listed prices are equal. |
| Generation speedtokens per second | Kimi K2.545 tok/s | Kimi K2.5 (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.52.38 s | Kimi K2.5 (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.5256K | Kimi K2.5 (Reasoning)128K | Kimi K2.5 lists the larger context window. |
Benchmark Deep Dive
AgenticTie19 benchmarks
| Benchmark | Kimi K2.5 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50.8% | 50.8% | Tie |
| BrowseCompSource | 60.6% | 60.6% | Tie |
| 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% | 95.9% | Tie |
| APEX-Agents-AASource | 11.5% | 11.5% | Tie |
| Gert LabsSource | 45.88% | 32.58% | Kimi K2.5 leads |
| ResearchClawBenchSource | 14.0% | — | Not comparable |
| JobBenchSource | 8.7% | — | Not comparable |
| AA Agentic IndexSource | 21.7% | 21.7% | Tie |
| GDPval-AASource | 25.4% | 25.4% | Tie |
| GDPval-AASource | 1009 | 1009 | Tie |
CodingKimi K2.5 (Reasoning) wins11 benchmarks
| Benchmark | Kimi K2.5 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 76.8% | 76.8% | Tie |
| 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 |
| AA-SciCodeSource | 49.0% | 49.0% | Tie |
| AA Coding IndexSource | 46.8% | 46.8% | Tie |
| Vibe Code BenchSource | — | 17.54% | Not comparable |
Reasoning3 benchmarks
KnowledgeKimi K2.5 (Reasoning) wins12 benchmarks
| Benchmark | Kimi K2.5 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| GPQASource | 87.6% | 87.6% | Tie |
| GPQA-DSource | 87.6% | — | Not comparable |
| SuperGPQASource | 69.2% | — | Not comparable |
| MMLU-ProSource | 87.1% | 87.1% | Tie |
| MMLU-Pro (Arcee)Source | 87.1% | — | Not comparable |
| HLESource | 30.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 35.4% | 35.4% | Tie |
| AA-GPQA DiamondSource | 87.9% | 87.9% | Tie |
| AA-HLESource | 29.4% | 29.4% | Tie |
| AA-Omniscience IndexSource | -8.1% | -8.1% | Tie |
| AA-Omniscience AccuracySource | 34.3% | 34.3% | Tie |
| AA-Omniscience Hallucination RateSource | 64.6% | 64.6% | Tie |
Math9 benchmarks
| Benchmark | Kimi K2.5 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AIME 2025Source | 96.1% | 96.1% | Tie |
| 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
MultimodalTie6 benchmarks
Frequently Asked Questions (5)
Which is better, Kimi K2.5 or Kimi K2.5 (Reasoning)?
Kimi K2.5 and Kimi K2.5 (Reasoning) are sibling variants in the Kimi K2.5 family, so the right pick depends on whether you value the better benchmark line, cheaper tokens, or the larger context window. Kimi K2.5 is ahead on BenchLM's BenchAlign leaderboard 59.66 to 59.35.
Which is better for knowledge tasks, Kimi K2.5 or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.2 versus 56.9. Kimi K2.5 stays close enough that the answer can still flip depending on your workload.
Which is better for coding, Kimi K2.5 or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 59.4. Kimi K2.5 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, Kimi K2.5 or Kimi K2.5 (Reasoning)?
Kimi K2.5 and Kimi K2.5 (Reasoning) are effectively tied for agentic tasks here, both landing at 55 on average.
Which is better for multimodal and grounded tasks, Kimi K2.5 or Kimi K2.5 (Reasoning)?
Kimi K2.5 and Kimi K2.5 (Reasoning) are effectively tied for multimodal and grounded tasks here, both landing at 78.5 on average.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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