Kimi K2 ThinkingMoonshot AI
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Span-01Respan
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Related Products
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About
Kimi K2 Thinking is an advanced open source reasoning model developed by Moonshot AI, designed specifically for long-horizon, multi-step workflows where the system interleaves chain-of-thought processes with tool invocation across hundreds of sequential tasks. The model uses a mixture-of-experts architecture with a total of 1 trillion parameters, yet only about 32 billion parameters are activated per inference pass, optimizing efficiency while maintaining vast capacity. It supports a context window of up to 256,000 tokens, enabling the handling of extremely long inputs and reasoning chains without losing coherence. Native INT4 quantization is built in, which reduces inference latency and memory usage without performance degradation. Kimi K2 Thinking is explicitly built for agentic workflows; it can autonomously call external tools, manage sequential logic steps (up to and typically between 200-300 tool calls in a single chain), and maintain consistent reasoning.
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About
Span-01 is a hyper-parallel reasoning classifier built to detect complex behaviors across long production traces in a single forward pass. Rather than generating tokens sequentially, it reasons over natural-language behavior definitions and returns direct probabilities for present, absent, and not_observable. The model is trained for general classification reasoning with RLAIF before being specialized for behavior detection, allowing it to apply previously unseen definitions to new behaviors and domains instead of relying on a fixed taxonomy. At inference time, hyper-parallel definition branches evaluate multiple behaviors against the same trace context simultaneously, while hybrid attention helps preserve reasoning over long, complex inputs. Span-01 is designed for production monitoring across safety, reliability, grounding, agent behavior, and response quality, including jailbreak and prompt injection detection, privacy, and secrets.
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Developers and AI research teams seeking a solution for building autonomous agents, multi-step reasoning systems and tool-enabled workflows
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Audience
AI, safety, evaluation, and observability teams seeking to detect and score complex behaviors across long production traces with fast, probability-based classification
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Open source
Free Version
Supported
Free Trial
Not Supported
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Pricing
$199 per month
Free Version
Supported
Free Trial
Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Company InformationMoonshot AI
Founded: 2023
United States
moonshotai.github.io/Kimi-K2/thinking.html
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Company InformationRespan
Founded: 2023
United States
www.respan.ai/blog/introducing-span-1
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Alternatives |
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Categories |
Categories |
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Integrations
AssemblyAI
Not Supported
GPT-5.1
Supported
GPT-5.2
Supported
GPT-5.2 Instant
Supported
GPT-5.2 Pro
Supported
GPT-5.3 Instant
Supported
GPT-5.4 nano
Supported
GPT-5.5
Supported
GPT-5.5 Pro
Supported
GPT-5.6 Luna
Supported
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Integrations
AssemblyAI
Supported
GPT-5.1
Not Supported
GPT-5.2
Not Supported
GPT-5.2 Instant
Not Supported
GPT-5.2 Pro
Not Supported
GPT-5.3 Instant
Not Supported
GPT-5.4 nano
Not Supported
GPT-5.5
Not Supported
GPT-5.5 Pro
Not Supported
GPT-5.6 Luna
Not Supported
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