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Model comparison

Kimi K2.6 vs MAI-Thinking-1

Data verified

Head-to-head evidence from 8 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

Kimi K2.6
Moonshot AI
56.79/100
No comparison
N/A
1 category wins3 category wins

Public leaderboard positions: Kimi K2.6 #74 (Estimated); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Kimi K2.6 and MAI-Thinking-1 share 8 comparable benchmark results. 4 of 8 categories are comparable. 43 results are unique to Kimi K2.6; 5 to MAI-Thinking-1.

Updated July 23, 2026
Shared results
8
Kimi K2.6 only
43
MAI-Thinking-1 only
5
Comparable categories
4 / 8

Treat this as a split decision. Kimi K2.6 makes more sense if agentic is the priority; MAI-Thinking-1 is the better fit if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 8 shared benchmark results across 4 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 K2.6 and MAI-Thinking-1 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.

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 K2.6 and MAI-Thinking-1
CategoryKimi K2.6ΔMAI-Thinking-1
KnowledgeKimi K2.642.2Margin→ 30.3MAI-Thinking-172.5
AgenticKimi K2.673.5Margin← 27.5MAI-Thinking-146.0
MathKimi K2.667.1Margin→ 22.6MAI-Thinking-189.7
CodingKimi K2.664.4Margin→ 1.1MAI-Thinking-165.5
MultimodalKimi K2.679.8MarginNo overlapMAI-Thinking-1Not measured
Inst. FollowingKimi K2.6Not measuredMarginNo overlapMAI-Thinking-185.0

Decisive benchmark drivers

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

More
A · Kimi K2.6B · MAI-Thinking-1

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 66.7%B 46%
    Winner: Kimi K2.6Δ 20.7
    Terminal-Bench 2.0: Kimi K2.6 scored 66.7%; MAI-Thinking-1 scored 46%. Kimi K2.6 wins this benchmark.

  2. HMMT Feb 2026

    Math
    Source ↗
    A 92.7%B 84.9%
    Winner: Kimi K2.6Δ 7.8
    HMMT Feb 2026: Kimi K2.6 scored 92.7%; MAI-Thinking-1 scored 84.9%. Kimi K2.6 wins this benchmark.

  3. SWE-bench Verified

    Coding
    Source ↗
    A 80.2%B 73.5%
    Winner: Kimi K2.6Δ 6.7
    SWE-bench Verified: Kimi K2.6 scored 80.2%; MAI-Thinking-1 scored 73.5%. Kimi K2.6 wins this benchmark.

  4. GPQA

    Knowledge
    Source ↗
    A 90.5%B 84.2%
    Winner: Kimi K2.6Δ 6.3
    GPQA: Kimi K2.6 scored 90.5%; MAI-Thinking-1 scored 84.2%. Kimi K2.6 wins this benchmark.

  5. SWE-bench Pro

    Coding
    Source ↗
    A 58.6%B 52.8%
    Winner: Kimi K2.6Δ 5.8
    SWE-bench Pro: Kimi K2.6 scored 58.6%; MAI-Thinking-1 scored 52.8%. Kimi K2.6 wins this benchmark.

Operational comparison

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

MetricKimi K2.6MAI-Thinking-1Comparison
Input / output priceUSD per 1M tokensKimi K2.6$0.95 input / $4 outputMAI-Thinking-1Not availableA complete price comparison is not available.
Generation speedtokens per secondKimi K2.6Not availableMAI-Thinking-1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenKimi K2.6Not availableMAI-Thinking-1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensKimi K2.6256KMAI-Thinking-1256KListed context windows are equal.

Benchmark Deep Dive

AgenticKimi K2.6 wins
BenchmarkKimi K2.6MAI-Thinking-1Result
Terminal-Bench 2.0Source 66.7%46%Kimi K2.6 leads
BrowseCompSource 83.2%—Not comparable
OSWorld-VerifiedSource 73.1%—Not comparable
ToolathlonSource 50%—Not comparable
MCP AtlasSource 55.9%—Not comparable
Claw-EvalSource 62.3%—Not comparable
DeepSearchQASource 92.5%—Not comparable
WideResearchSource 80.8%—Not comparable
AA Agentic IndexSource 30.3%—Not comparable
τ²-bench resultsSource 95.9%—Not comparable
GDPval-AASource 34.5%—Not comparable
GDPval-AASource 1189—Not comparable
APEX-Agents-AASource 28.5%—Not comparable
Gert LabsSource 56.82%—Not comparable
ResearchClawBenchSource 18.0%—Not comparable
OSWorld 2.0Source 4.6%—Not comparable
terminalBenchHardSource 43.9%—Not comparable
CodingMAI-Thinking-1 wins
BenchmarkKimi K2.6MAI-Thinking-1Result
SWE-bench VerifiedSource 80.2%73.5%Kimi K2.6 leads
LiveCodeBench v6Source 89.6%—Not comparable
SWE-bench ProSource 58.6%52.8%Kimi K2.6 leads
SWE MultilingualSource 76.7%—Not comparable
SciCodeSource 52.2%—Not comparable
Terminal-Bench 2.0Source 66.7%46.0%Kimi K2.6 leads
Vibe Code BenchSource 37.89%—Not comparable
cursorBench31Source 47.6%—Not comparable
AA Coding IndexSource 61.8%—Not comparable
AA-SciCodeSource 53.5%—Not comparable
Reasoning
BenchmarkKimi K2.6MAI-Thinking-1Result
AA-LCRSource 69.7%—Not comparable
CritPtSource 8.0%—Not comparable
Graphwalks BFS 128KSource —90%Not comparable
KnowledgeMAI-Thinking-1 wins
BenchmarkKimi K2.6MAI-Thinking-1Result
GPQASource 90.5%84.2%Kimi K2.6 leads
GPQA-DSource 90.5%84.2%Kimi K2.6 leads
HLESource 34.7%—Not comparable
Artificial Analysis Intelligence IndexSource 44.2%—Not comparable
AA-GPQA DiamondSource 91.1%—Not comparable
AA-HLESource 35.9%—Not comparable
AA-Omniscience IndexSource 6.4%—Not comparable
AA-Omniscience AccuracySource 32.8%—Not comparable
AA-Omniscience Hallucination RateSource 39.3%—Not comparable
MMLU-ProSource —85%Not comparable
SimpleQASource —31%Not comparable
MathMAI-Thinking-1 wins
BenchmarkKimi K2.6MAI-Thinking-1Result
AIME26Source 96.4%94.5%Kimi K2.6 leads
HMMT Feb 2026Source 92.7%84.9%Kimi K2.6 leads
MMAnswerBenchSource 86.0%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 38.966%—Not comparable
FrontierMath v2 (Tier 4)Source 14.580%—Not comparable
AIME 2025Source —97%Not comparable
Multimodal
BenchmarkKimi K2.6MAI-Thinking-1Result
MMMU-ProSource 79.4%—Not comparable
MMMU-Pro w/ PythonSource 80.1%—Not comparable
CharXivSource 80.4%—Not comparable
MathVisionSource 87.4%—Not comparable
V*Source 96.9%—Not comparable
AA-MMMU-ProSource 79.4%—Not comparable
Design Arena WebsiteSource 1306—Not comparable
Inst. Following
BenchmarkKimi K2.6MAI-Thinking-1Result
AA-IFBenchSource 76.0%—Not comparable
IFBenchSource —85%Not comparable
Frequently Asked Questions (5)

Which is better, Kimi K2.6 or MAI-Thinking-1?

Kimi K2.6 and MAI-Thinking-1 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, Kimi K2.6 or MAI-Thinking-1?

MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 42.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, Kimi K2.6 or MAI-Thinking-1?

MAI-Thinking-1 has the edge for coding in this comparison, averaging 65.5 versus 64.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Which is better for math, Kimi K2.6 or MAI-Thinking-1?

MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 67.1. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Kimi K2.6 or MAI-Thinking-1?

Kimi K2.6 has the edge for agentic tasks in this comparison, averaging 73.5 versus 46. Inside this category, Terminal-Bench 2.0 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 K2.6
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
MAI-Thinking-1
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Model the full break-even

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