\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

Benchmark	^{Kimi K2.5} (Thinking)	^GPT-5.2 (xhigh)	^{Claude 4.5 Opus} (Extended Thinking)	^{Gemini 3 Pro} (High Thinking Level)	^{DeepSeek V3.2} (Thinking)	^{Qwen3-VL- 235B-A22B- Thinking}
Reasoning & Knowledge
HLE-Full	30.1	34.5	30.8	37.5	25.1^†	-
HLE-Full (w/ tools)	50.2	45.5	43.2	45.8	40.8^†	-
AIME 2025	96.1	100	92.8	95.0	93.1	-
HMMT 2025 (Feb)	95.4	99.4	92.9*	97.3*	92.5	-
IMO-AnswerBench	81.8	86.3	78.5*	83.1*	78.3	-
GPQA-Diamond	87.6	92.4	87.0	91.9	82.4	-
MMLU-Pro	87.1	86.7*	89.3*	90.1	85.0	-
Image & Video
MMMU-Pro	78.5	79.5*	74.0	81.0	-	69.3
CharXiv (RQ)	77.5	82.1	67.2*	81.4	-	66.1
MathVision	84.2	83.0	77.1*	86.1*	-	74.6
MathVista (mini)	90.1	82.8*	80.2*	89.8*	-	85.8
ZeroBench	9	9*	3*	8*	-	4*
ZeroBench (w/ tools)	11	7*	9*	12*	-	3*
OCRBench	92.3	80.7*	86.5*	90.3*	-	87.5
OmniDocBench 1.5	88.8	85.7	87.7*	88.5	-	82.0*
InfoVQA (val)	92.6	84*	76.9*	57.2*	-	89.5
SimpleVQA	71.2	55.8*	69.7*	69.7*	-	56.8*
WorldVQA	46.3	28.0	36.8	47.4	-	23.5
VideoMMMU	86.6	85.9	84.4*	87.6	-	80.0
MMVU	80.4	80.8*	77.3	77.5	-	71.1
MotionBench	70.4	64.8	60.3	70.3	-	-
VideoMME	87.4	86.0*	-	88.4*	-	79.0
LongVideoBench	79.8	76.5*	67.2*	77.7*	-	65.6*
LVBench	75.9	-	-	73.5*	-	63.6
Coding
SWE-Bench Verified	76.8	80.0	80.9	76.2	73.1	-
SWE-Bench Pro	50.7	55.6	55.4*	-	-	-
SWE-Bench Multilingual	73.0	72.0	77.5	65.0	70.2	-
Terminal Bench 2.0	50.8	54.0	59.3	54.2	46.4	-
PaperBench	63.5	63.7*	72.9*	-	47.1	-
CyberGym	41.3	-	50.6	39.9*	17.3*	-
SciCode	48.7	52.1	49.5	56.1	38.9	-
OJBench (cpp)	57.4	-	54.6*	68.5*	54.7*	-
LiveCodeBench (v6)	85.0	-	82.2*	87.4*	83.3	-
Long Context
Longbench v2	61.0	54.5*	64.4*	68.2*	59.8*	-
AA-LCR	70.0	72.3*	71.3*	65.3*	64.3*	-
Agentic Search
BrowseComp	60.6	65.8	37.0	37.8	51.4	-
BrowseComp (w/ctx manage)	74.9	57.8	59.2	67.6	-
BrowseComp (Agent Swarm)	78.4	-	-	-	-	-
WideSearch (item-f1)	72.7	-	76.2*	57.0	32.5*	-
WideSearch (item-f1 Agent Swarm)	79.0	-	-	-	-	-
DeepSearchQA	77.1	71.3*	76.1*	63.2*	60.9*	-
FinSearchCompT2&T3	67.8	-	66.2*	49.9	59.1*	-
Seal-0	57.4	45.0	47.7*	45.5*	49.5*	-

","licenseDescription","Use of the Moonshot AI Kimi-K2.5 model as an Azure Direct Model is subject to the terms of the Modified MIT License, available at .","license","other","deploymentOptions","UnifiedEndpointMaaS","isDirectFromAzure","02/05/2026 17:00:00 +00:00","modelCapabilities","reasoning, streaming","pricingLink","https://aka.ms/MoonshotAIPricing","datasets",[],"sampleInputData","sampleOutputData","resourceRequirements","stage","Development","systemCatalogData",{"_777":643,"_764":778,"_781":782,"_758":759,"_783":784,"_785":-5,"_786":-5,"_787":-5,"_788":-5,"_789":-5,"_745":790,"_740":741,"_324":739,"_742":791,"_744":791,"_747":792,"_749":794,"_795":-5,"_796":797,"_799":-5,"_800":-5,"_801":-5,"_802":-5,"_803":-5,"_804":80,"_805":80,"_806":12,"_807":-5,"_808":-5,"_160":-5,"_809":-5,"_768":-5,"_810":-5,"_152":811,"_756":757,"_814":-5,"_754":815,"_752":753,"_816":-5,"_817":-5,"_818":-5,"_819":-5,"_820":-5,"_821":-5,"_822":-5,"_823":-5,"_824":-5,"_825":-5,"_826":-5,"_827":-5,"_828":80,"_829":-5,"_830":-5,"_762":12,"_831":-5,"_832":-5,"_833":-5,"_834":-5,"_835":-5,"_338":-5,"_836":-5,"_837":-5,"_838":-5,"_839":-5,"_840":-5,"_841":-5,"_842":-5,"_843":-5,"_844":-5,"_845":-5,"_846":-5,"_847":-5,"_848":-5,"_849":-5,"_850":-5,"_851":-5,"_852":-5},"publisher",[779,780],"reasoning","streaming","deploymentTypes",[734],"inferenceTasks",[736],"fineTuningTasks","fineTuningMethods","inferenceComputeAllowed","fineTuneComputeAllowed","evaluationComputeAllowed",[746],262144,[750,793],"image",[750],"playgroundRateLimitTier","azureOffers",[798],"standard-paygo","inferenceRetirementDate","finetuneDeprecationDate","finetuneRetirementDate","inferenceDeprecationDate","inferenceLegacyDate","enableMaap","enableBatch","maasInference","maasFineTuning","featured","benchmark","industry",[812,813],"Reasoning","Multilingual","trainingDataDate","

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

Benchmark	^{Kimi K2.5} (Thinking)	^GPT-5.2 (xhigh)	^{Claude 4.5 Opus} (Extended Thinking)	^{Gemini 3 Pro} (High Thinking Level)	^{DeepSeek V3.2} (Thinking)	^{Qwen3-VL- 235B-A22B- Thinking}
Reasoning & Knowledge
HLE-Full	30.1	34.5	30.8	37.5	25.1^†	-
HLE-Full (w/ tools)	50.2	45.5	43.2	45.8	40.8^†	-
AIME 2025	96.1	100	92.8	95.0	93.1	-
(High) \| Claude Sonnet 4.5 (Thinking) \| K2 0905 \| DeepSeek-V3.2 \| Grok-4 \|\n\|:----------:\|:--------:\|:------------:\|:------:\|:----------------------------:\|:--------:\|:--------------:\|:-------:\|\n\| HLE (Text-only) \| no tools \| 23.9 \| 26.3 \| 19.8* \| 7.9 \| 19.8 \| 25.4 \|\n\| \| w/ tools \| 44.9 \| 41.7* \| 32.0* \| 21.7 \| 20.3* \| 41.0 \|\n\| \| heavy \| 51.0 \| 42.0 \| - \| - \| - \| 50.7 \|\n\| AIME25 \| no tools \| 94.5 \| 94.6 \| 87.0 \| 51.0 \| 89.3 \| 91.7 \|\n\| \| w/ python \| 99.1 \| 99.6 \| 100.0 \| 75.2 \| 58.1* \| 98.8 \|\n\| \| heavy \| 100.0 \| 100.0 \| - \| - \| - \| 100.0 \|\n\| HMMT25 \| no tools \| 89.4 \| 93.3 \| 74.6* \| 38.8 \| 83.6 \| 90.0 \|\n\| \| w/ python \| 95.1 \| 96.7 \| 88.8* \| 70.4 \| 49.5* \| 93.9 \|\n\| \| heavy \| 97.5 \| 100.0 \| - \| - \| - \| 96.7 \|\n\| IMO-AnswerBench \| no tools \| 78.6 \| 76.0* \| 65.9* \| 45.8 \| 76.0* \| 73.1 \|\n\| GPQA \| no tools \| 84.5 \| 85.7 \| 83.4 \| 74.2 \| 79.9 \| 87.5 \|\n\nGeneral Tasks\n\n\| Benchmark \| Setting \| K2 Thinking \| GPT-5 (High) \| Claude Sonnet 4.5 (Thinking) \| K2 0905 \| DeepSeek-V3.2 \|\n\|:----------:\|:--------:\|:------------:\|:------:\|:----------------------------:\|:--------:\|:--------------:\|\n\| MMLU-Pro \| no tools \| 84.6 \| 87.1 \| 87.5 \| 81.9 \| 85.0 \|\n\| MMLU-Redux \| no tools \| 94.4 \| 95.3 \| 95.6 \| 92.7 \| 93.7 \|\n\| Longform Writing \| no tools \| 73.8 \| 71.4 \| 79.8 \| 62.8 \| 72.5 \|\n\| HealthBench \| no tools \| 58.0 \| 67.2 \| 44.2 \| 43.8 \| 46.9 \|\n\nAgentic Search Tasks\n\n\| Benchmark \| Setting \| K2 Thinking \| GPT-5 (High) \| Claude Sonnet 4.5 (Thinking) \| K2 0905 \| DeepSeek-V3.2 \|\n\|:----------:\|:--------:\|:------------:\|:------:\|:----------------------------:\|:--------:\|:--------------:\|\n\| BrowseComp \| w/ tools \| 60.2 \| 54.9 \| 24.1 \| 7.4 \| 40.1 \|\n\| BrowseComp-ZH \| w/ tools \| 62.3 \| 63.0* \| 42.4* \| 22.2 \| 47.9 \|\n\| Seal-0 \| w/ tools \| 56.3 \| 51.4* \| 53.4* \| 25.2 \| 38.5* \|\n\| FinSearchComp-T3 \| w/ tools \| 47.4 \| 48.5* \| 44.0* \| 10.4 \| 27.0* \|\n\| Frames \| w/ tools \| 87.0 \| 86.0* \| 85.0* \| 58.1 \| 80.2* \|\n\nCoding Tasks\n\n\| Benchmark \| Setting \| K2 Thinking \| GPT-5 (High) \| Claude Sonnet 4.5 (Thinking) \| K2 0905 \| DeepSeek-V3.2 \|\n\|:----------:\|:--------:\|:------------:\|:------:\|:----------------------------:\|:--------:\|:--------------:\|\n\| SWE-bench Verified \| w/ tools \| 71.3 \| 74.9 \| 77.2 \| 69.2 \| 67.8 \|\n\| SWE-bench Multilingual \| w/ tools \| 61.1 \| 55.3* \| 68.0 \| 55.9 \| 57.9 \|\n\| Multi-SWE-bench \| w/ tools \| 41.9 \| 39.3* \| 44.3 \| 33.5 \| 30.6 \|\n\| SciCode \| no tools \| 44.8 \| 42.9 \| 44.7 \| 30.7 \| 37.7 \|\n\| LiveCodeBenchV6 \| no tools \| 83.1 \| 87.0* \| 64.0* \| 56.1* \| 74.1 \|\n\| OJ-Bench (cpp) \| no tools \| 48.7 \| 56.2* \| 30.4* \| 25.5* \| 38.2* \|\n\| Terminal-Bench \| w/ simulated tools (JSON) \| 47.1 \| 43.8 \| 51.0 \| 44.5 \| 37.7 \|\n\n# Benchmarking methodology\nSource: MoonshotAI\n\nThe provider has not supplied this information.\n\n# Public data summary\nSource: MoonshotAI\n\nThe provider has not supplied this information.","Use of the Moonshot AI Kimi-K2-Thinking model as an Azure Direct Model is subject to the terms of the Modified MIT License, available at .","12/08/2025 17:00:00 +00:00",[],{"_777":643,"_764":954,"_781":955,"_758":759,"_783":956,"_785":-5,"_786":-5,"_787":-5,"_788":-5,"_789":-5,"_745":957,"_740":947,"_324":946,"_742":791,"_744":791,"_747":958,"_749":959,"_795":-5,"_796":960,"_799":-5,"_800":-5,"_801":-5,"_802":-5,"_803":-5,"_804":80,"_805":80,"_806":12,"_807":-5,"_808":-5,"_160":-5,"_809":-5,"_768":-5,"_810":-5,"_152":961,"_756":950,"_814":-5,"_754":962,"_752":948,"_816":-5,"_817":-5,"_818":-5,"_819":-5,"_820":-5,"_821":-5,"_822":-5,"_823":-5,"_824":-5,"_825":-5,"_826":-5,"_827":-5,"_828":80,"_829":-5,"_830":-5,"_762":12,"_831":-5,"_832":-5,"_833":-5,"_834":-5,"_835":-5,"_338":-5,"_836":-5,"_837":-5,"_838":-5,"_839":-5,"_840":-5,"_841":-5,"_842":-5,"_843":-5,"_844":-5,"_845":-5,"_846":-5,"_847":-5,"_848":-5,"_849":-5,"_850":-5,"_851":-5,"_852":-5},[779,780],[734],[736],[746],[750],[750],[798],[812,813],"\n# Quality and performance evaluations\n\nReasoning Tasks\n\n\| Benchmark \| Setting \| K2 Thinking \| GPT-5 (High) \| Claude Sonnet 4.5 (Thinking) \| K2 0905 \| DeepSeek-V3.2 \| Grok-4 \|\n\|:----------:\|:--------:\|:------------:\|:------:\|:----------------------------:\|:--------:\|:--------------:\|:-------:\|\n\| HLE (Text-only) \| no tools \| 23.9 \| 26.3 \| 19.8* \| 7.9 \| 19.8 \| 25.4 \|\n\| \| w/ tools \| 44.9 \| 41.7* \| 32.0* \| 21.7 \| 20.3* \| 41.0 \|\n\| \| heavy \| 51.0 \| 42.0 \| - \| - \| - \| 50.7 \|\n\| AIME25 \| no tools \| 94.5 \| 94.6 \| 87.0 \| 51.0 \| 89.3 \| 91.7 \|\n\| \| w/ python \| 99.1 \| 99.6 \| 100.0 \| 75.2 \| 58.1* \| 98.8 \|\n\| \| heavy \| 100.0 \| 100.0 \| - \| - \| - \| 100.0 \|\n\| HMMT25 \| no tools \| 89.4 \| 93.3 \| 74.6* \| 38.8 \| 83.6 \| 90.0 \|\n\| \| w/ python \| 95.1 \| 96.7 \| 88.8* \| 70.4 \| 49.5* \| 93.9 \|\n\| \| heavy \| 97.5 \| 100.0 \| - \| - \| - \| 96.7 \|\n\| IMO-AnswerBench \| no tools \| 78.6 \| 76.0* \| 65.9* \| 45.8 \| 76.0* \| 73.1 \|\n\| GPQA \| no tools \| 84.5 \| 85.7 \| 83.4 \| 74.2 \| 79.9 \| 87.5 \|\n\nGeneral Tasks\n\n\| Benchmark \| Setting \| K2 Thinking \| GPT-5 (High) \| Claude Sonnet 4.5 (Thinking) \| K2 0905 \| DeepSeek-V3.2 \|\n\|:----------:\|:--------:\|:------------:\|:------:\|:----------------------------:\|:--------:\|:--------------:\|\n\| MMLU-Pro \| no tools \| 84.6 \| 87.1 \| 87.5 \| 81.9 \| 85.0 \|\n\| MMLU-Redux \| no tools \| 94.4 \| 95.3 \| 95.6 \| 92.7 \| 93.7 \|\n\| Longform Writing \| no tools \| 73.8 \| 71.4 \| 79.8 \| 62.8 \| 72.5 \|\n\| HealthBench \| no tools \| 58.0 \| 67.2 \| 44.2 \| 43.8 \| 46.9 \|\n\nAgentic Search Tasks\n\n\| Benchmark \| Setting \| K2 Thinking \| GPT-5 (High) \| Claude Sonnet 4.5 (Thinking) \| K2 0905 \| DeepSeek-V3.2 \|\n\|:----------:\|:--------:\|:------------:\|:------:\|:----------------------------:\|:--------:\|:--------------:\|\n\| BrowseComp \| w/ tools \| 60.2 \| 54.9 \| 24.1 \| 7.4 \| 40.1 \|\n\| BrowseComp-ZH \| w/ tools \| 62.3 \| 63.0* \| 42.4* \| 22.2 \| 47.9 \|\n\| Seal-0 \| w/ tools \| 56.3 \| 51.4* \| 53.4* \| 25.2 \| 38.5* \|\n\| FinSearchComp-T3 \| w/ tools \| 47.4 \| 48.5* \|","# Direct from Azure models\n Direct from Azure models are a select portfolio curated for their market-differentiated capabilities:\n\n- Secure and managed by Microsoft: Purchase and manage models directly through Azure with a single license, consistent support, and no third-party dependencies, backed by Azure's enterprise-grade infrastructure.\n- Streamlined operations: Benefit from unified billing, governance, and seamless PTU portability across models hosted on Azure - all as part of one Microsoft Foundry platform.\n- Future-ready flexibility: Access the latest models as they become available, and easily test, deploy, or switch between them within Microsoft Foundry; reducing integration effort.\n- Cost control and optimization: Scale on demand with pay-as-you-go flexibility or reserve PTUs for predictable performance and savings.\n\nLearn more about [Direct from Azure models](https://aka.ms/DirectfromAzure).\n\n# Key capabilities\n\n## About this model\n\nKimi K2 Thinking is the latest, most capable version of open-source thinking model. Starting with Kimi K2, we built it as a thinking agent that reasons step-by-step while dynamically invoking tools. It sets a new state-of-the-art on Humanity's Last Exam (HLE), BrowseComp, and other benchmarks by dramatically scaling multi-step reasoning depth and maintaining stable tool-use across 200–300 sequential calls. At the same time, K2 Thinking is a native INT4 quantization model with 256k context window, achieving lossless reductions in inference latency and GPU memory usage.\n\n## Key model capabilities\n\n- Deep Thinking & Tool Orchestration: End-to-end trained to interleave chain-of-thought reasoning with function calls, enabling autonomous research, coding, and writing workflows that last hundreds of steps without drift.\n- Native INT4 Quantization: Quantization-Aware Training (QAT) is employed in post-training stage to achieve lossless 2x speed-up in low-latency mode.\n- Stable Long-Horizon Agency: Maintains coherent goal-directed behavior across up to 200–300 consecutive tool invocations, surpassing prior models that degrade after 30–50 steps.\n\n# Use cases\nSee Responsible AI for additional considerations for responsible use.\n\n## Key use cases\n\nThe provider has not supplied this information.\n\n## Out of scope use cases\n\nThe provider has not supplied this information.\n\n# Pricing\nPricing is based on a number of factors, including deployment type and tokens used. [See pricing details here.](https://aka.ms/MoonshotAIPricing)\n\n# Technical specs\n\n\| \| \|\n\|:---:\|:---:\|\n\| Architecture \| Mixture-of-Experts (MoE) \|\n\| Total Parameters \| 1T \|\n\| Activated Parameters \| 32B \|\n\| Number of Layers (Dense layer included) \| 61 \|\n\| Number of Dense Layers \| 1 \|\n\| Attention Hidden Dimension \| 7168 \|\n\| MoE Hidden Dimension (per Expert) \| 2048 \|\n\| Number of Attention Heads \| 64 \|\n\| Number of Experts \| 384 \|\n\| Selected Experts per Token \| 8 \|\n\| Number of Shared Experts \| 1 \|\n\| Vocabulary Size \| 160K \|\n\| Context Length \| 256K \|\n\| Attention Mechanism \| MLA \|\n\| Activation Function \| SwiGLU \|\n\n## Training cut-off date\n\nThe provider has not supplied this information.\n\n## Training time\n\nThe provider has not supplied this information.\n\n## Input formats\n\nThe provider has not supplied this information.\n\n## Output formats\n\nThe provider has not supplied this information.\n\n## Supported languages\n\nThe provider has not supplied this information.\n\n## Sample JSON response\n\nThe provider has not supplied this information.\n\n## Model architecture\n\nThe provider has not supplied this information.\n\n## Long context\n\nThe provider has not supplied this information.\n\n## Optimizing model performance\n\nThe provider has not supplied this information.\n\n## Additional assets\n\nPlease see MoonshotAI's Kimi-K2-Thinking model card here.\n\n# Training disclosure\n\n## Training, testing and validation\n\nThe provider has not supplied this information.\n\n# Distribution\n\n## Distribution channels\n\nThe provider has not supplied this information.\n\n# More information\n\nThe provider has not supplied this information.\n\n\n\n",[856,857,858],{"_861":862,"_863":966,"_875":969,"_93":946,"_877":878,"_879":-5,"_880":881,"_882":684,"_883":884,"_885":-5,"_887":888,"_889":970,"_891":80,"_892":-5,"_893":-5,"_894":-5,"_895":-5,"_896":971,"_903":80,"_904":-5,"_906":972,"_908":-5,"_909":910},{"_865":967,"_867":968,"_874":-5},"2025-12-02T13:30:54.9560709+00:00",{"_869":870,"_871":870,"_872":714,"_873":-5},"Kimi-K2-Thinking:1","2025-12-17T07:25:38.1906531Z",{"_745":898,"_899":900,"_901":902},{"_777":900},{},29,[976],{"_925":926,"_927":-5,"_928":977,"_930":916,"_931":-5,"_917":932},"azureml://registries/azureml-moonshotai-staging/models/kimi-k2-thinking/versions/1","azureml://registries/azureml-moonshotai/models/Kimi-K2-Thinking/versions/1",{"_707":689,"_936":980},70.82,"nextSkip","continuationToken","entityContainerIdsToEntityContainerMetadata",{"_714":985},{"_986":714,"_987":988,"_989":990,"_991":714,"_992":921,"_993":994,"_1076":1077,"_1078":918,"_1079":12,"_1080":12},"resourceId","subscriptionId","dc6198eb-4af0-4a8d-bbbb-98b0e9fc21eb","resourceGroup","registry-builtin-moonshotai-eastus","resourceName","entityContainerType","regions",[995,998,1000,1002,1004,1006,1008,1010,1012,1014,1016,1018,1020,1022,1024,1026,1028,1030,1032,1034,1036,1038,1040,1042,1044,1046,1048,1050,1052,1054,1056,1058,1060,1062,1064,1066,1068,1070,1072,1074],{"_996":6,"_997":12},"regionName","isPrimaryRegion",{"_996":999,"_997":80},"australiaeast",{"_996":1001,"_997":80},"australiasoutheast",{"_996":1003,"_997":80},"brazilsouth",{"_996":1005,"_997":80},"canadacentral",{"_996":1007,"_997":80},"canadaeast",{"_996":1009,"_997":80},"centralindia",{"_996":1011,"_997":80},"centralus",{"_996":1013,"_997":80},"eastasia",{"_996":1015,"_997":80},"eastus2",{"_996":1017,"_997":80},"francecentral",{"_996":1019,"_997":80},"germanywestcentral",{"_996":1021,"_997":80},"japaneast",{"_996":1023,"_997":80},"japanwest",{"_996":1025,"_997":80},"jioindiawest",{"_996":1027,"_997":80},"koreacentral",{"_996":1029,"_997":80},"northcentralus",{"_996":1031,"_997":80},"northeurope",{"_996":1033,"_997":80},"norwayeast",{"_996":1035,"_997":80},"southafricanorth",{"_996":1037,"_997":80},"southcentralus",{"_996":1039,"_997":80},"southeastasia",{"_996":1041,"_997":80},"swedencentral",{"_996":1043,"_997":80},"switzerlandnorth",{"_996":1045,"_997":80},"uaenorth",{"_996":1047,"_997":80},"uksouth",{"_996":1049,"_997":80},"ukwest",{"_996":1051,"_997":80},"westcentralus",{"_996":1053,"_997":80},"westeurope",{"_996":1055,"_997":80},"westus",{"_996":1057,"_997":80},"westus2",{"_996":1059,"_997":80},"westus3",{"_996":1061,"_997":80},"qatarcentral",{"_996":1063,"_997":80},"polandcentral",{"_996":1065,"_997":80},"southindia",{"_996":1067,"_997":80},"switzerlandwest",{"_996":1069,"_997":80},"italynorth",{"_996":1071,"_997":80},"spaincentral",{"_996":1073,"_997":80},"israelcentral",{"_996":1075,"_997":80},"eastus2euap","tenantId","33e01921-4d64-4f8c-a055-5bdaffd5e33d","immutableResourceId","isPublicResource","isTradeRestrictedResource","resourcesNotQueriedReasons",{},"numberOfEntityContainersNotQueried","fanoutData","regionalFanoutState","shardErrors",{},"canSupportSkip","facets",1770623755234,[777,1092,560,560],"moonshot ai","[\"publisher\",\"moonshot ai\",\"\",\"\"]","actionData","errors"]