Model comparison
DeepSeek V4 Pro (High) vs Kimi K2.5
Head-to-head evidence from 28 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro (High) #81 (Estimated); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (High) and Kimi K2.5 share 28 comparable benchmark results. 4 of 8 categories are comparable. 10 results are unique to DeepSeek V4 Pro (High); 35 to Kimi K2.5.
Updated July 23, 2026- Shared results
- 28
- DeepSeek V4 Pro (High) only
- 10
- Kimi K2.5 only
- 35
- Comparable categories
- 4 / 8
Pick Kimi K2.5 if you want the stronger benchmark profile. DeepSeek V4 Pro (High) only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 28 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 is clearly ahead on the BenchAlign aggregate, 59.66 to 55.47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (High). That is roughly 3.4x on output cost alone. DeepSeek V4 Pro (High) 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. DeepSeek V4 Pro (High) 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 | DeepSeek V4 Pro (High) | Δ | Kimi K2.5 |
|---|---|---|---|
| Math | DeepSeek V4 Pro (High)94.0 | Margin← 33.4 | Kimi K2.560.6 |
| Agentic | DeepSeek V4 Pro (High)70.6 | Margin← 15.6 | Kimi K2.555.0 |
| Coding | DeepSeek V4 Pro (High)69.8 | Margin← 10.4 | Kimi K2.559.4 |
| Knowledge | DeepSeek V4 Pro (High)57.0 | Margin← 0.1 | Kimi K2.556.9 |
| Reasoning | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | Kimi K2.561.0 |
| Multilingual | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | Kimi K2.582.3 |
| Multimodal | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | Kimi K2.578.5 |
| Inst. Following | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | Kimi K2.593.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 80.4%B 60.6%Winner: DeepSeek V4 Pro (High)Δ 19.8BrowseComp: DeepSeek V4 Pro (High) scored 80.4%; Kimi K2.5 scored 60.6%. DeepSeek V4 Pro (High) wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 63.3%B 50.8%Winner: DeepSeek V4 Pro (High)Δ 12.5Terminal-Bench 2.0: DeepSeek V4 Pro (High) scored 63.3%; Kimi K2.5 scored 50.8%. DeepSeek V4 Pro (High) wins this benchmark. - Source ↗
HMMT Feb 2026
MathA 94.0%B 87.1%Winner: DeepSeek V4 Pro (High)Δ 6.9HMMT Feb 2026: DeepSeek V4 Pro (High) scored 94.0%; Kimi K2.5 scored 87.1%. DeepSeek V4 Pro (High) wins this benchmark. - Source ↗
HLE
KnowledgeA 34.5%B 30.1%Winner: DeepSeek V4 Pro (High)Δ 4.4HLE: DeepSeek V4 Pro (High) scored 34.5%; Kimi K2.5 scored 30.1%. DeepSeek V4 Pro (High) wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 54.4%B 50.7%Winner: DeepSeek V4 Pro (High)Δ 3.7SWE-bench Pro: DeepSeek V4 Pro (High) scored 54.4%; Kimi K2.5 scored 50.7%. DeepSeek V4 Pro (High) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro (High) | Kimi K2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (High)$0.435 input / $0.87 output | Kimi K2.5$0.6 input / $3 output | DeepSeek V4 Pro (High) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Pro (High)Not available | Kimi K2.545 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (High)Not available | Kimi K2.52.38 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (High)1M | Kimi K2.5256K | DeepSeek V4 Pro (High) lists the larger context window. |
Benchmark Deep Dive
AgenticDeepSeek V4 Pro (High) wins20 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.3% | 50.8% | DeepSeek V4 Pro (High) leads |
| BrowseCompSource | 80.4% | 60.6% | DeepSeek V4 Pro (High) leads |
| HLE w/ toolsSource | 44.7% | — | Not comparable |
| MCP AtlasSource | 74.2% | 29.5% | DeepSeek V4 Pro (High) leads |
| ToolathlonSource | 49% | 27.8% | DeepSeek V4 Pro (High) leads |
| τ²-bench resultsSource | 94.2% | 95.9% | Kimi K2.5 leads |
| GDPval-AASource | 39.9% | 25.4% | DeepSeek V4 Pro (High) leads |
| GDPval-AASource | 1299 | 1009 | DeepSeek V4 Pro (High) leads |
| AA Agentic IndexSource | 34.4% | 21.7% | DeepSeek V4 Pro (High) leads |
| 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 |
| MCP-TasksSource | — | 59.1% | Not comparable |
| WideResearchSource | — | 72.7% | 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 |
CodingDeepSeek V4 Pro (High) wins12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.5 | Result |
|---|---|---|---|
| CodeforcesSource | 2919.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79.4% | 76.8% | DeepSeek V4 Pro (High) leads |
| SWE-bench ProSource | 54.4% | 50.7% | DeepSeek V4 Pro (High) leads |
| SWE MultilingualSource | 74.1% | 73% | DeepSeek V4 Pro (High) leads |
| Terminal-Bench 2.0Source | 63.3% | — | Not comparable |
| AA-SciCodeSource | 46.4% | 49.0% | Kimi K2.5 leads |
| AA Coding IndexSource | 58.7% | 46.8% | DeepSeek V4 Pro (High) leads |
| SWE-bench Verified*Source | — | 70.8% | Not comparable |
| LiveCodeBench v6Source | — | 85.0% | Not comparable |
| SWE-RebenchSource | — | 58.5% | Not comparable |
| React Native EvalsSource | — | 77.2% | Not comparable |
| SciCodeSource | — | 48.7% | Not comparable |
Reasoning5 benchmarks
KnowledgeDeepSeek V4 Pro (High) wins14 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.5 | Result |
|---|---|---|---|
| MMLU-ProSource | 87.1% | 87.1% | Tie |
| SimpleQASource | 46.2% | — | Not comparable |
| Chinese-SimpleQASource | 77.7% | — | Not comparable |
| GPQASource | 89.1% | 87.6% | DeepSeek V4 Pro (High) leads |
| GPQA-DSource | 89.1% | 87.6% | DeepSeek V4 Pro (High) leads |
| HLESource | 34.5% | 30.1% | DeepSeek V4 Pro (High) leads |
| Artificial Analysis Intelligence IndexSource | 43.1% | 35.4% | DeepSeek V4 Pro (High) leads |
| AA-GPQA DiamondSource | 90.5% | 87.9% | DeepSeek V4 Pro (High) leads |
| AA-HLESource | 33.5% | 29.4% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience IndexSource | -9.7% | -8.1% | Kimi K2.5 leads |
| AA-Omniscience AccuracySource | 41.8% | 34.3% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience Hallucination RateSource | 88.6% | 64.6% | Kimi K2.5 leads |
| SuperGPQASource | — | 69.2% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 87.1% | Not comparable |
MathDeepSeek V4 Pro (High) wins12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.5 | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 94.0% | 87.1% | DeepSeek V4 Pro (High) leads |
| IMOAnswerBenchSource | 88.0% | — | Not comparable |
| ApexSource | 27.4% | — | Not comparable |
| Apex ShortlistSource | 85.5% | — | Not comparable |
| 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 |
| 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 (5)
Which is better, DeepSeek V4 Pro (High) or Kimi K2.5?
Kimi K2.5 is ahead on BenchLM's BenchAlign leaderboard, 59.66 to 55.47. The biggest single separator in this matchup is BrowseComp, where the scores are 80.4% and 60.6%.
Which is better for knowledge tasks, DeepSeek V4 Pro (High) or Kimi K2.5?
DeepSeek V4 Pro (High) has the edge for knowledge tasks in this comparison, averaging 57 versus 56.9. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro (High) or Kimi K2.5?
DeepSeek V4 Pro (High) has the edge for coding in this comparison, averaging 69.8 versus 59.4. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Pro (High) or Kimi K2.5?
DeepSeek V4 Pro (High) has the edge for math in this comparison, averaging 94 versus 60.6. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Pro (High) or Kimi K2.5?
DeepSeek V4 Pro (High) has the edge for agentic tasks in this comparison, averaging 70.6 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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