Skip to main content
BenchLM
Advertise

Model comparison

DeepSeek V4 Flash (Max) vs Kimi K2.5

Data verified

Head-to-head evidence from 28 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

N/A
No comparison
Kimi K2.5
Moonshot AI
59.66/100
3 category wins1 category wins

Public leaderboard positions: DeepSeek V4 Flash (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 Flash (Max) and Kimi K2.5 share 28 comparable benchmark results. 4 of 8 categories are comparable. 17 results are unique to DeepSeek V4 Flash (Max); 35 to Kimi K2.5.

Updated July 23, 2026
Shared results
28
DeepSeek V4 Flash (Max) only
17
Kimi K2.5 only
35
Comparable categories
4 / 8

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

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

DeepSeek V4 Flash (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 $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (Max). That is roughly 10.7x on output cost alone. DeepSeek V4 Flash (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 Flash (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 Flash (Max) and Kimi K2.5
CategoryDeepSeek V4 Flash (Max)ΔKimi K2.5
MathDeepSeek V4 Flash (Max)94.8Margin← 34.2Kimi K2.560.6
CodingDeepSeek V4 Flash (Max)68.8Margin← 9.4Kimi K2.559.4
AgenticDeepSeek V4 Flash (Max)63.8Margin← 8.8Kimi K2.555.0
KnowledgeDeepSeek V4 Flash (Max)55.3Margin→ 1.6Kimi K2.556.9
ReasoningDeepSeek V4 Flash (Max)Not measuredMarginNo overlapKimi K2.561.0
MultilingualDeepSeek V4 Flash (Max)Not measuredMarginNo overlapKimi K2.582.3
MultimodalDeepSeek V4 Flash (Max)Not measuredMarginNo overlapKimi K2.578.5
Inst. FollowingDeepSeek V4 Flash (Max)Not measuredMarginNo overlapKimi K2.593.9

Decisive benchmark drivers

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

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

  1. BrowseComp

    Agentic
    Source ↗
    A 73.2%B 60.6%
    Winner: DeepSeek V4 Flash (Max)Δ 12.6
    BrowseComp: DeepSeek V4 Flash (Max) scored 73.2%; Kimi K2.5 scored 60.6%. DeepSeek V4 Flash (Max) wins this benchmark.

  2. HMMT Feb 2026

    Math
    Source ↗
    A 94.8%B 87.1%
    Winner: DeepSeek V4 Flash (Max)Δ 7.7
    HMMT Feb 2026: DeepSeek V4 Flash (Max) scored 94.8%; Kimi K2.5 scored 87.1%. DeepSeek V4 Flash (Max) wins this benchmark.

  3. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 56.9%B 50.8%
    Winner: DeepSeek V4 Flash (Max)Δ 6.1
    Terminal-Bench 2.0: DeepSeek V4 Flash (Max) scored 56.9%; Kimi K2.5 scored 50.8%. DeepSeek V4 Flash (Max) wins this benchmark.

  4. HLE

    Knowledge
    Source ↗
    A 34.8%B 30.1%
    Winner: DeepSeek V4 Flash (Max)Δ 4.7
    HLE: DeepSeek V4 Flash (Max) scored 34.8%; Kimi K2.5 scored 30.1%. DeepSeek V4 Flash (Max) wins this benchmark.

  5. SWE-bench Verified

    Coding
    Source ↗
    A 79%B 76.8%
    Winner: DeepSeek V4 Flash (Max)Δ 2.2
    SWE-bench Verified: DeepSeek V4 Flash (Max) scored 79%; Kimi K2.5 scored 76.8%. DeepSeek V4 Flash (Max) wins this benchmark.

Operational comparison

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

MetricDeepSeek V4 Flash (Max)Kimi K2.5Comparison
Input / output priceUSD per 1M tokensDeepSeek V4 Flash (Max)$0.14 input / $0.28 outputKimi K2.5$0.6 input / $3 outputDeepSeek V4 Flash (Max) has the lower combined listed price.
Generation speedtokens per secondDeepSeek V4 Flash (Max)Not availableKimi K2.545 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V4 Flash (Max)Not availableKimi K2.52.38 sA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V4 Flash (Max)1MKimi K2.5256KDeepSeek V4 Flash (Max) lists the larger context window.

Benchmark Deep Dive

AgenticDeepSeek V4 Flash (Max) wins
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
Terminal-Bench 2.0Source 56.9%50.8%DeepSeek V4 Flash (Max) leads
BrowseCompSource 73.2%60.6%DeepSeek V4 Flash (Max) leads
HLE w/ toolsSource 45.1%—Not comparable
MCP AtlasSource 69%29.5%DeepSeek V4 Flash (Max) leads
GDPval-AASource 11891009DeepSeek V4 Flash (Max) leads
ToolathlonSource 47.8%27.8%DeepSeek V4 Flash (Max) leads
AA Agentic IndexSource 31.1%21.7%DeepSeek V4 Flash (Max) leads
τ²-bench resultsSource 95%95.9%Kimi K2.5 leads
GDPval-AASource 34.4%25.4%DeepSeek V4 Flash (Max) leads
AA BriefcaseSource 831—Not comparable
AA EnterpriseOps-GymSource 39.6%—Not comparable
AA Harvey LABSource 81.3%—Not comparable
AA ITBenchSource 31.5%—Not comparable
AA Tau3 BankingSource 22.9%—Not comparable
terminalBenchHardSource 35.6%—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
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 Flash (Max) wins
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
CodeforcesSource 3052.0—Not comparable
SWE-bench VerifiedSource 79%76.8%DeepSeek V4 Flash (Max) leads
SWE-bench ProSource 52.6%50.7%DeepSeek V4 Flash (Max) leads
SWE MultilingualSource 73.3%73%DeepSeek V4 Flash (Max) leads
Terminal-Bench 2.0Source 56.9%—Not comparable
AA Coding IndexSource 56.2%46.8%DeepSeek V4 Flash (Max) leads
AA-SciCodeSource 44.9%49.0%Kimi K2.5 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
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
MRCR 1MSource 78.7%—Not comparable
CorpusQA 1MSource 60.5%—Not comparable
AA-LCRSource 63.0%65.3%Kimi K2.5 leads
CritPtSource 7.1%3.1%DeepSeek V4 Flash (Max) leads
LongBench v2Source —61%Not comparable
KnowledgeKimi K2.5 wins
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
MMLU-ProSource 86.2%87.1%Kimi K2.5 leads
SimpleQASource 34.1%—Not comparable
Chinese-SimpleQASource 78.9%—Not comparable
GPQASource 88.1%87.6%DeepSeek V4 Flash (Max) leads
GPQA-DSource 88.1%87.6%DeepSeek V4 Flash (Max) leads
HLESource 34.8%30.1%DeepSeek V4 Flash (Max) leads
Artificial Analysis Intelligence IndexSource 40.3%35.4%DeepSeek V4 Flash (Max) leads
AA-GPQA DiamondSource 89.4%87.9%DeepSeek V4 Flash (Max) leads
AA-HLESource 32.1%29.4%DeepSeek V4 Flash (Max) leads
AA-Omniscience IndexSource -22.9%-8.1%Kimi K2.5 leads
AA-Omniscience AccuracySource 37.2%34.3%DeepSeek V4 Flash (Max) leads
AA-Omniscience Hallucination RateSource 95.8%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 Flash (Max) wins
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
HMMT Feb 2026Source 94.8%87.1%DeepSeek V4 Flash (Max) leads
IMOAnswerBenchSource 88.4%—Not comparable
ApexSource 33.0%—Not comparable
Apex ShortlistSource 85.7%—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
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
MMLU-ProXSource —82.3%Not comparable
NOVA-63Source —56.0%Not comparable
Multimodal
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
Design Arena WebsiteSource 12381279Kimi 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
BenchmarkDeepSeek V4 Flash (Max)Kimi K2.5Result
AA-IFBenchSource 79.2%70.2%DeepSeek V4 Flash (Max) leads
IFEvalSource —93.9%Not comparable
Frequently Asked Questions (5)

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

DeepSeek V4 Flash (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 Flash (Max) or Kimi K2.5?

Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 56.9 versus 55.3. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, DeepSeek V4 Flash (Max) or Kimi K2.5?

DeepSeek V4 Flash (Max) has the edge for coding in this comparison, averaging 68.8 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 Flash (Max) or Kimi K2.5?

DeepSeek V4 Flash (Max) has the edge for math in this comparison, averaging 94.8 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 Flash (Max) or Kimi K2.5?

DeepSeek V4 Flash (Max) has the edge for agentic tasks in this comparison, averaging 63.8 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 Flash (Max)
API / mo$315
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

Related Comparisons

Explore More

DeepSeek Compare Pricing Methodology Find Your Best LLM Overall Rankings
Last updated: July 23, 2026

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.