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Model comparison

Kimi K2.5 vs MiMo-V2.5-Pro

Data verified

Head-to-head evidence from 23 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

Moonshot AI
59.66/100
Margin
10.5pts
winning →
70.19/100
2 category wins1 category wins

Public leaderboard positions: Kimi K2.5 #54 (Supported); MiMo-V2.5-Pro #14 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Kimi K2.5 and MiMo-V2.5-Pro share 23 comparable benchmark results. 3 of 8 categories are comparable. 40 results are unique to Kimi K2.5; 8 to MiMo-V2.5-Pro.

Updated July 21, 2026
Shared results
23
Kimi K2.5 only
40
MiMo-V2.5-Pro only
8
Comparable categories
3 / 8

Pick MiMo-V2.5-Pro if you want the stronger benchmark profile. Kimi K2.5 only becomes the better choice 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 23 shared benchmark results across 6 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

MiMo-V2.5-Pro is clearly ahead on the BenchAlign aggregate, 70.19 to 59.66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

MiMo-V2.5-Pro's sharpest advantage is in agentic, where it averages 68.4 against 55. The single biggest benchmark swing on the page is HLE, 30.1% to 48%. Kimi K2.5 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

MiMo-V2.5-Pro 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. MiMo-V2.5-Pro 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 Kimi K2.5 and MiMo-V2.5-Pro
CategoryKimi K2.5ΔMiMo-V2.5-Pro
AgenticKimi K2.555.0Margin 13.4MiMo-V2.5-Pro68.4
KnowledgeKimi K2.556.9Margin 8.9MiMo-V2.5-Pro48.0
CodingKimi K2.559.4Margin 2.2MiMo-V2.5-Pro57.2
ReasoningKimi K2.561.0MarginNo overlapMiMo-V2.5-ProNot measured
MathKimi K2.560.6MarginNo overlapMiMo-V2.5-ProNot measured
MultilingualKimi K2.582.3MarginNo overlapMiMo-V2.5-ProNot measured
MultimodalKimi K2.578.5MarginNo overlapMiMo-V2.5-ProNot measured
Inst. FollowingKimi K2.593.9MarginNo overlapMiMo-V2.5-ProNot measured

Decisive benchmark drivers

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

More
A · Kimi K2.5B · MiMo-V2.5-Pro
  1. HLE

    Knowledge
    Source ↗
    A 30.1%B 48%
    Winner: MiMo-V2.5-ProΔ 17.9
    HLE: Kimi K2.5 scored 30.1%; MiMo-V2.5-Pro scored 48%. MiMo-V2.5-Pro wins this benchmark.
  2. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 50.8%B 68.4%
    Winner: MiMo-V2.5-ProΔ 17.6
    Terminal-Bench 2.0: Kimi K2.5 scored 50.8%; MiMo-V2.5-Pro scored 68.4%. MiMo-V2.5-Pro wins this benchmark.
  3. SWE-bench Pro

    Coding
    Source ↗
    A 50.7%B 57.2%
    Winner: MiMo-V2.5-ProΔ 6.5
    SWE-bench Pro: Kimi K2.5 scored 50.7%; MiMo-V2.5-Pro scored 57.2%. MiMo-V2.5-Pro wins this benchmark.

Operational comparison

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

MetricKimi K2.5MiMo-V2.5-ProComparison
Input / output priceUSD per 1M tokensKimi K2.5$0.6 input / $3 outputMiMo-V2.5-ProNot availableA complete price comparison is not available.
Generation speedtokens per secondKimi K2.545 tok/sMiMo-V2.5-ProNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenKimi K2.52.38 sMiMo-V2.5-ProNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensKimi K2.5256KMiMo-V2.5-Pro1MMiMo-V2.5-Pro lists the larger context window.

Benchmark Deep Dive

AgenticMiMo-V2.5-Pro wins
BenchmarkKimi K2.5MiMo-V2.5-ProResult
Terminal-Bench 2.0Source 50.8%68.4%MiMo-V2.5-Pro leads
BrowseCompSource 60.6%Not comparable
Claw-EvalSource 52.3%63.8%MiMo-V2.5-Pro leads
QwenClawBenchSource 54.3%Not comparable
τ³-bench resultsSource 65.7%72.9%MiMo-V2.5-Pro leads
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%94.2%Kimi K2.5 leads
APEX-Agents-AASource 11.5%2.4%Kimi K2.5 leads
Gert LabsSource 45.88%62.70%MiMo-V2.5-Pro leads
ResearchClawBenchSource 14.0%Not comparable
JobBenchSource 8.7%Not comparable
AA Agentic IndexSource 21.7%29.1%MiMo-V2.5-Pro leads
GDPval-AASource 25.4%38.3%MiMo-V2.5-Pro leads
GDPval-AASource 10091265MiMo-V2.5-Pro leads
AA BriefcaseSource 873Not comparable
AA ITBenchSource 38.2%Not comparable
terminalBenchHardSource 43.2%Not comparable
aaTerminalBench21Source 65.2%Not comparable
AA Harvey LABSource 73.3%Not comparable
CodingKimi K2.5 wins
BenchmarkKimi K2.5MiMo-V2.5-ProResult
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%57.2%MiMo-V2.5-Pro leads
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%50.2%MiMo-V2.5-Pro leads
AA Coding IndexSource 46.8%60.2%MiMo-V2.5-Pro leads
Terminal-Bench 2.0Source 68.4%Not comparable
Reasoning
BenchmarkKimi K2.5MiMo-V2.5-ProResult
LongBench v2Source 61%Not comparable
AA-LCRSource 65.3%73.3%MiMo-V2.5-Pro leads
CritPtSource 3.1%4.0%MiMo-V2.5-Pro leads
KnowledgeKimi K2.5 wins
BenchmarkKimi K2.5MiMo-V2.5-ProResult
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%48%MiMo-V2.5-Pro leads
Artificial Analysis Intelligence IndexSource 35.4%42.2%MiMo-V2.5-Pro leads
AA-GPQA DiamondSource 87.9%86.6%Kimi K2.5 leads
AA-HLESource 29.4%33.8%MiMo-V2.5-Pro leads
AA-Omniscience IndexSource -8.1%3.6%MiMo-V2.5-Pro leads
AA-Omniscience AccuracySource 34.3%22.6%Kimi K2.5 leads
AA-Omniscience Hallucination RateSource 64.6%24.5%MiMo-V2.5-Pro leads
HLE w/o toolsSource 34%Not comparable
AA Openness IndexSource 38.9%Not comparable
Math
BenchmarkKimi K2.5MiMo-V2.5-ProResult
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
Multilingual
BenchmarkKimi K2.5MiMo-V2.5-ProResult
MMLU-ProXSource 82.3%Not comparable
NOVA-63Source 56.0%Not comparable
Multimodal
BenchmarkKimi K2.5MiMo-V2.5-ProResult
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
Design Arena WebsiteSource 12791298MiMo-V2.5-Pro leads
Inst. Following
BenchmarkKimi K2.5MiMo-V2.5-ProResult
IFEvalSource 93.9%Not comparable
AA-IFBenchSource 70.2%79.9%MiMo-V2.5-Pro leads
Frequently Asked Questions (4)

Which is better, Kimi K2.5 or MiMo-V2.5-Pro?

MiMo-V2.5-Pro is ahead on BenchLM's BenchAlign leaderboard, 70.19 to 59.66. The biggest single separator in this matchup is HLE, where the scores are 30.1% and 48%.

Which is better for knowledge tasks, Kimi K2.5 or MiMo-V2.5-Pro?

Kimi K2.5 has the edge for knowledge tasks in this comparison, averaging 56.9 versus 48. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, Kimi K2.5 or MiMo-V2.5-Pro?

Kimi K2.5 has the edge for coding in this comparison, averaging 59.4 versus 57.2. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Kimi K2.5 or MiMo-V2.5-Pro?

MiMo-V2.5-Pro has the edge for agentic tasks in this comparison, averaging 68.4 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.

Kimi K2.5
API / mo$2,700
Self-host / mo$5,221
Break-even132M/day
MiMo-V2.5-Pro
API / mo$0
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

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Last updated: July 21, 2026

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