Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
MAI-Thinking-1 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Kimi K2.6 vs MAI-Thinking-1
Updated October 20, 2026. Rank says Kimi K2.6 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Share or export
Decision reading
Kimi K2.6 has the higher public point estimate, 58.38 versus 53.1. Their conditional score ranges overlap. These ranges do not establish rank confidence. 9 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 9
- Kimi K2.6 only
- 28
- MAI-Thinking-1 only
- 4
- Like-for-like categories
- 0 / 8
Estimated: Kimi K2.6 and MAI-Thinking-1. Conditional ranges do not establish rank confidence.How the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
MAI-Thinking-1 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documentedChat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-ratesRepository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
43.1Kimi K2.6—MAI-Thinking-1
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
28 Kimi K2.6 only
9 Shared
4 MAI-Thinking-1 only
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
Terminal-Bench 2.0Agentic
Normalized gap 20.7Kimi K2.6:66.7%MAI-Thinking-1:46%HMMT Feb 2026Math
Normalized gap 7.8Kimi K2.6:92.7%MAI-Thinking-1:84.9%SWE-bench VerifiedCoding
Normalized gap 6.7Kimi K2.6:80.2%MAI-Thinking-1:73.5%GPQAKnowledge
Normalized gap 6.3Kimi K2.6:90.5%MAI-Thinking-1:84.2%SWE-bench ProCoding
Normalized gap 5.8Kimi K2.6:58.6%MAI-Thinking-1:52.8%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Knowledge
Directional only- Kimi K2.6
- 60.3
- Supported · #49/187
- MAI-Thinking-1
- 55.5
- Estimated · #59/187
- Basis
- BenchAlign v5.8 lane · 5 vs 3 public rows
- Reading
- Directional only
Agentic
Not comparable- Kimi K2.6
- 44.2
- Supported · #61/131
- MAI-Thinking-1
- Not ranked
- Basis
- BenchAlign v5.8 lane · 12 vs 1 public rows
- Reading
- Not comparable
Coding
Not comparable- Kimi K2.6
- 43.1
- Supported · #59/152
- MAI-Thinking-1
- Not ranked
- Basis
- BenchAlign v5.8 lane · 10 vs 4 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Kimi K2.6
- Not ranked
- MAI-Thinking-1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Kimi K2.6
- 73.8
- #27/55
- MAI-Thinking-1
- Not ranked
- Basis
- Provisional lane · 2 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Kimi K2.6
- Not ranked
- MAI-Thinking-1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Kimi K2.6
- Not ranked
- MAI-Thinking-1
- 94.7
- #3/149
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- Kimi K2.6
- 76.8
- #4/12
- MAI-Thinking-1
- 81.1
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 4 vs 2 weighted rows
- Reading
- Not comparable
| Category | Kimi K2.6 | MAI-Thinking-1 | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 60.3Supported · #49/187 | 55.5Estimated · #59/187 | Directional onlyBenchAlign v5.8 lane · 5 vs 3 public rows | Directional only |
| Agentic | 44.2Supported · #61/131 | Not ranked | Not comparableBenchAlign v5.8 lane · 12 vs 1 public rows | Not comparable |
| Coding | 43.1Supported · #59/152 | Not ranked | Not comparableBenchAlign v5.8 lane · 10 vs 4 public rows | Not comparable |
| Reasoning | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 73.8#27/55 | Not ranked | Not comparableProvisional lane · 2 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 94.7#3/149 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Math | 76.8#4/12 | 81.1Unranked · 3 rankable rows | Not comparableProvisional lane · 4 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Kimi K2.6
- $0.00295
- Fits in one request
- MAI-Thinking-1
- API rate not published
- Fits in one request
MAI-Thinking-1 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Kimi K2.6
- $0.0595
- Fits in one request
- MAI-Thinking-1
- API rate not published
- Fits in one request
MAI-Thinking-1 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Kimi K2.6
- $0.091
- Fits in one request
- MAI-Thinking-1
- API rate not published
- Fits in one request
- Cached-input rate unavailable
MAI-Thinking-1 has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationKimi K2.6MAI-Thinking-1
Context window
Maximum documented context; output-token limits may be lower.
Kimi K2.6
256K
MAI-Thinking-1
256K
API model ID
Kimi K2.6
Not sourced
MAI-Thinking-1
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Kimi K2.6
$0.16 per 1M cached input tokens
MAI-Thinking-1
No comparable hosted API rate
Documented inputs
Kimi K2.6
Not sourced
MAI-Thinking-1
Not sourced
Documented outputs
Kimi K2.6
Not sourced
MAI-Thinking-1
Not sourced
Provider availability
Kimi K2.6
Not sourced
MAI-Thinking-1
Not sourced
Reasoning profile
Kimi K2.6
Reasoning
MAI-Thinking-1
Reasoning
Weight access
Kimi K2.6
Open Weight
MAI-Thinking-1
Proprietary
License
Kimi K2.6
Open Weight
MAI-Thinking-1
Proprietary
Release date
Kimi K2.6
2026-04-20
MAI-Thinking-1
2026-06-02
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Kimi K2.6 has the higher public point estimate, 58.38 versus 53.1. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Both models list 256K.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Kimi K2.6 or MAI-Thinking-1?
Kimi K2.6 has the higher public point estimate, 58.38 versus 53.1. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Kimi K2.6 or MAI-Thinking-1?
MAI-Thinking-1 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Kimi K2.6 or MAI-Thinking-1?
MAI-Thinking-1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Kimi K2.6 or MAI-Thinking-1?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Kimi K2.6 or MAI-Thinking-1?
Both models list the same context window, 256K.
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$27,962
Break-even500M/day
MAI-Thinking-1
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence41 rows
Agentic
Terminal-Bench 2.0
Kimi K2.666.7%SourceMAI-Thinking-146%SourceKimi K2.6 leads this result
BrowseComp
Kimi K2.683.2%SourceMAI-Thinking-1—Not directly comparable
OSWorld-Verified
Kimi K2.673.1%SourceMAI-Thinking-1—Not directly comparable
Toolathlon
Kimi K2.650%SourceMAI-Thinking-1—Not directly comparable
MCP Atlas
Kimi K2.655.9%SourceMAI-Thinking-1—Not directly comparable
Claw-Eval
Kimi K2.662.3%SourceMAI-Thinking-1—Not directly comparable
DeepSearchQA
Kimi K2.692.5%SourceMAI-Thinking-1—Not directly comparable
WideResearch
Kimi K2.680.8%SourceMAI-Thinking-1—Not directly comparable
Gert Labs
Kimi K2.656.82%SourceMAI-Thinking-1—Not directly comparable
ResearchClawBench
Kimi K2.618.0%SourceMAI-Thinking-1—Not directly comparable
OSWorld 2.0
Kimi K2.64.6%SourceMAI-Thinking-1—Not directly comparable
Terminal-Bench 2.1 (Vals)
Kimi K2.653.6%SourceMAI-Thinking-1—Not directly comparable
Coding
SWE-bench Verified
Kimi K2.680.2%SourceMAI-Thinking-173.5%SourceKimi K2.6 leads this result
LiveCodeBench v6
Kimi K2.689.6%SourceMAI-Thinking-187.7%SourceKimi K2.6 leads this result
SWE-bench Pro
Kimi K2.658.6%SourceMAI-Thinking-152.8%SourceKimi K2.6 leads this result
SWE Multilingual
Kimi K2.676.7%SourceMAI-Thinking-1—Not directly comparable
SciCode
Kimi K2.652.2%SourceMAI-Thinking-1—Not directly comparable
Terminal-Bench 2.0
Kimi K2.666.7%SourceMAI-Thinking-146.0%SourceKimi K2.6 leads this result
Vibe Code Bench
Kimi K2.637.89%SourceMAI-Thinking-1—Not directly comparable
cursorBench31
Kimi K2.647.6%SourceMAI-Thinking-1—Not directly comparable
LiveCodeBench (Vals)
Kimi K2.686.8%SourceMAI-Thinking-1—Not directly comparable
SWE-bench (Vals)
Kimi K2.676.2%SourceMAI-Thinking-1—Not directly comparable
Reasoning
Graphwalks BFS 128K
Kimi K2.6—MAI-Thinking-190%SourceNot directly comparable
Multimodal
MMMU-Pro
Kimi K2.679.4%SourceMAI-Thinking-1—Not directly comparable
MMMU-Pro w/ Python
Kimi K2.680.1%SourceMAI-Thinking-1—Not directly comparable
CharXiv
Kimi K2.680.4%SourceMAI-Thinking-1—Not directly comparable
MathVision
Kimi K2.687.4%SourceMAI-Thinking-1—Not directly comparable
V*
Kimi K2.696.9%SourceMAI-Thinking-1—Not directly comparable
Knowledge
GPQA
Kimi K2.690.5%SourceMAI-Thinking-184.2%SourceKimi K2.6 leads this result
GPQA-D
Kimi K2.690.5%SourceMAI-Thinking-184.2%SourceKimi K2.6 leads this result
HLE
Kimi K2.634.7%SourceMAI-Thinking-1—Not directly comparable
GPQA Diamond (Vals)
Kimi K2.689.1%SourceMAI-Thinking-1—Not directly comparable
MMLU-Pro (Vals)
Kimi K2.687.6%SourceMAI-Thinking-1—Not directly comparable
MMLU-Pro
Kimi K2.6—MAI-Thinking-185%SourceNot directly comparable
Instruction following
IFBench
Kimi K2.6—MAI-Thinking-185%SourceNot directly comparable
Math
AIME26
Kimi K2.696.4%SourceMAI-Thinking-194.5%SourceKimi K2.6 leads this result
HMMT Feb 2026
Kimi K2.692.7%SourceMAI-Thinking-184.9%SourceKimi K2.6 leads this result
MMAnswerBench
Kimi K2.686.0%SourceMAI-Thinking-1—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Kimi K2.657.193%SourceMAI-Thinking-1—Not directly comparable
FrontierMath v2 (Tier 4)
Kimi K2.625.641%SourceMAI-Thinking-1—Not directly comparable
AIME 2025
Kimi K2.6—MAI-Thinking-197%SourceNot directly comparable
41 public results · 9 shared
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Last updated October 20, 2026