Model comparison

DeepSeek V4 Pro (Max) vs Kimi K2.5

Data verified July 23, 2026

Head-to-head evidence from 29 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

DeepSeek V4 Pro (Max)

DeepSeek

N/A

No comparison

Kimi K2.5

Moonshot AI

59.66/100

4 category wins0 category wins

Public leaderboard positions: DeepSeek V4 Pro (Max) unranked (Not scored); Kimi K2.5 #54 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V4 Pro (Max) and Kimi K2.5 share 29 comparable benchmark results. 4 of 8 categories are comparable. 19 results are unique to DeepSeek V4 Pro (Max); 34 to Kimi K2.5.

Updated July 23, 2026

Shared results: 29
DeepSeek V4 Pro (Max) only: 19
Kimi K2.5 only: 34
Comparable categories: 4 / 8

Treat this as a split decision. DeepSeek V4 Pro (Max) makes more sense if mathematics is the priority or you want the cheaper token bill; Kimi K2.5 is the better fit if you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 29 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

DeepSeek V4 Pro (Max) and Kimi K2.5 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

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 (Max). That is roughly 3.4x on output cost alone. DeepSeek V4 Pro (Max) 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 (Max) 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 scores and score margins for DeepSeek V4 Pro (Max) and Kimi K2.5
Category	DeepSeek V4 Pro (Max)	Δ	Kimi K2.5
Math	DeepSeek V4 Pro (Max)95.2	Margin← 34.6	Kimi K2.560.6
Agentic	DeepSeek V4 Pro (Max)74.5	Margin← 19.5	Kimi K2.555.0
Coding	DeepSeek V4 Pro (Max)70.9	Margin← 11.5	Kimi K2.559.4
Knowledge	DeepSeek V4 Pro (Max)60.1	Margin← 3.2	Kimi K2.556.9
Reasoning	DeepSeek V4 Pro (Max)Not measured	MarginNo overlap	Kimi K2.561.0
Multilingual	DeepSeek V4 Pro (Max)Not measured	MarginNo overlap	Kimi K2.582.3
Multimodal	DeepSeek V4 Pro (Max)Not measured	MarginNo overlap	Kimi K2.578.5
Inst. Following	DeepSeek V4 Pro (Max)Not measured	MarginNo overlap	Kimi K2.593.9

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

A · DeepSeek V4 Pro (Max)B · Kimi K2.5

BrowseComp
Agentic
Source ↗
A 83.4%B 60.6%
Winner: DeepSeek V4 Pro (Max)Δ 22.8
BrowseComp: DeepSeek V4 Pro (Max) scored 83.4%; Kimi K2.5 scored 60.6%. DeepSeek V4 Pro (Max) wins this benchmark.
Terminal-Bench 2.0
Agentic
Source ↗
A 67.9%B 50.8%
Winner: DeepSeek V4 Pro (Max)Δ 17.1
Terminal-Bench 2.0: DeepSeek V4 Pro (Max) scored 67.9%; Kimi K2.5 scored 50.8%. DeepSeek V4 Pro (Max) wins this benchmark.
HMMT Feb 2026
Math
Source ↗
A 95.2%B 87.1%
Winner: DeepSeek V4 Pro (Max)Δ 8.1
HMMT Feb 2026: DeepSeek V4 Pro (Max) scored 95.2%; Kimi K2.5 scored 87.1%. DeepSeek V4 Pro (Max) wins this benchmark.
HLE
Knowledge
Source ↗
A 37.7%B 30.1%
Winner: DeepSeek V4 Pro (Max)Δ 7.6
HLE: DeepSeek V4 Pro (Max) scored 37.7%; Kimi K2.5 scored 30.1%. DeepSeek V4 Pro (Max) wins this benchmark.
SWE-bench Pro
Coding
Source ↗
A 55.4%B 50.7%
Winner: DeepSeek V4 Pro (Max)Δ 4.7
SWE-bench Pro: DeepSeek V4 Pro (Max) scored 55.4%; Kimi K2.5 scored 50.7%. DeepSeek V4 Pro (Max) wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

Metric	DeepSeek V4 Pro (Max)	Kimi K2.5	Comparison
Input / output priceUSD per 1M tokens	DeepSeek V4 Pro (Max)$0.435 input / $0.87 output	Kimi K2.5$0.6 input / $3 output	DeepSeek V4 Pro (Max) has the lower combined listed price.
Generation speedtokens per second	DeepSeek V4 Pro (Max)Not available	Kimi K2.545 tok/s	A complete speed comparison is not available.
First-answer latencyseconds to first token	DeepSeek V4 Pro (Max)Not available	Kimi K2.52.38 s	A complete latency comparison is not available.
Context windowmaximum listed tokens	DeepSeek V4 Pro (Max)1M	Kimi K2.5256K	DeepSeek V4 Pro (Max) lists the larger context window.

Benchmark Deep Dive

AgenticDeepSeek V4 Pro (Max) wins

27 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
Terminal-Bench 2.0Source	67.9%	50.8%	DeepSeek V4 Pro (Max) leads
BrowseCompSource	83.4%	60.6%	DeepSeek V4 Pro (Max) leads
HLE w/ toolsSource	48.2%	—	Not comparable
MCP AtlasSource	73.6%	29.5%	DeepSeek V4 Pro (Max) leads
GDPval-AASource	1307	1009	DeepSeek V4 Pro (Max) leads
ToolathlonSource	51.8%	27.8%	DeepSeek V4 Pro (Max) leads
AA Agentic IndexSource	36.4%	21.7%	DeepSeek V4 Pro (Max) leads
APEX-Agents-AASource	24.3%	11.5%	DeepSeek V4 Pro (Max) leads
τ²-bench resultsSource	96.2%	95.9%	DeepSeek V4 Pro (Max) leads
GDPval-AASource	40.4%	25.4%	DeepSeek V4 Pro (Max) leads
AA BriefcaseSource	932	—	Not comparable
AA EnterpriseOps-GymSource	40.4%	—	Not comparable
AA Harvey LABSource	84.4%	—	Not comparable
AA ITBenchSource	38.3%	—	Not comparable
AA Tau3 BankingSource	25.8%	—	Not comparable
terminalBenchHardSource	46.2%	—	Not comparable
aaTerminalBench21Source	64%	—	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
MCP-TasksSource	—	59.1%	Not comparable
WideResearchSource	—	72.7%	Not comparable
Gert LabsSource	—	45.88%	Not comparable
ResearchClawBenchSource	—	14.0%	Not comparable
JobBenchSource	—	8.7%	Not comparable

CodingDeepSeek V4 Pro (Max) wins

13 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
CodeforcesSource	3206.0	—	Not comparable
SWE-bench VerifiedSource	80.6%	76.8%	DeepSeek V4 Pro (Max) leads
SWE-bench ProSource	55.4%	50.7%	DeepSeek V4 Pro (Max) leads
SWE MultilingualSource	76.2%	73%	DeepSeek V4 Pro (Max) leads
Terminal-Bench 2.0Source	67.9%	—	Not comparable
Vibe Code BenchSource	49.93%	—	Not comparable
AA Coding IndexSource	59.4%	46.8%	DeepSeek V4 Pro (Max) leads
AA-SciCodeSource	50.0%	49.0%	DeepSeek V4 Pro (Max) 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

Reasoning

5 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
MRCR 1MSource	83.5%	—	Not comparable
CorpusQA 1MSource	62.0%	—	Not comparable
AA-LCRSource	66.3%	65.3%	DeepSeek V4 Pro (Max) leads
CritPtSource	12.9%	3.1%	DeepSeek V4 Pro (Max) leads
LongBench v2Source	—	61%	Not comparable

KnowledgeDeepSeek V4 Pro (Max) wins

15 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
MMLU-ProSource	87.5%	87.1%	DeepSeek V4 Pro (Max) leads
SimpleQASource	57.9%	—	Not comparable
Chinese-SimpleQASource	84.4%	—	Not comparable
GPQASource	90.1%	87.6%	DeepSeek V4 Pro (Max) leads
GPQA-DSource	90.1%	87.6%	DeepSeek V4 Pro (Max) leads
HLESource	37.7%	30.1%	DeepSeek V4 Pro (Max) leads
Artificial Analysis Intelligence IndexSource	44.3%	35.4%	DeepSeek V4 Pro (Max) leads
AA-GPQA DiamondSource	88.8%	87.9%	DeepSeek V4 Pro (Max) leads
AA-HLESource	35.9%	29.4%	DeepSeek V4 Pro (Max) leads
AA-Omniscience IndexSource	-10.0%	-8.1%	Kimi K2.5 leads
AA-Omniscience AccuracySource	43.3%	34.3%	DeepSeek V4 Pro (Max) leads
AA-Omniscience Hallucination RateSource	94.0%	64.6%	Kimi K2.5 leads
AA Openness IndexSource	50.0%	—	Not comparable
SuperGPQASource	—	69.2%	Not comparable
MMLU-Pro (Arcee)Source	—	87.1%	Not comparable

MathDeepSeek V4 Pro (Max) wins

12 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
HMMT Feb 2026Source	95.2%	87.1%	DeepSeek V4 Pro (Max) leads
IMOAnswerBenchSource	89.8%	—	Not comparable
ApexSource	38.3%	—	Not comparable
Apex ShortlistSource	90.2%	—	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

Multilingual

2 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
MMLU-ProXSource	—	82.3%	Not comparable
NOVA-63Source	—	56.0%	Not comparable

Multimodal

6 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
Design Arena WebsiteSource	1264	1279	Kimi K2.5 leads
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%	Not comparable

Inst. Following

2 benchmarks

Benchmark	DeepSeek V4 Pro (Max)	Kimi K2.5	Result
AA-IFBenchSource	76.5%	70.2%	DeepSeek V4 Pro (Max) leads
IFEvalSource	—	93.9%	Not comparable

Frequently Asked Questions (5)

Which is better, DeepSeek V4 Pro (Max) or Kimi K2.5?

DeepSeek V4 Pro (Max) and Kimi K2.5 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, DeepSeek V4 Pro (Max) or Kimi K2.5?

DeepSeek V4 Pro (Max) has the edge for knowledge tasks in this comparison, averaging 60.1 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 (Max) or Kimi K2.5?

DeepSeek V4 Pro (Max) has the edge for coding in this comparison, averaging 70.9 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 (Max) or Kimi K2.5?

DeepSeek V4 Pro (Max) has the edge for math in this comparison, averaging 95.2 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 (Max) or Kimi K2.5?

DeepSeek V4 Pro (Max) has the edge for agentic tasks in this comparison, averaging 74.5 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.

DeepSeek V4 Pro (Max)

API / mo$979

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Kimi K2.5

API / mo$2,700

Self-host / mo$5,221

Break-even132M/day

Model the full break-even

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