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  5. Kimi K3

Kimi K3

Kimi K3 is a frontier-scale native multimodal Mixture-of-Experts model designed for long-horizon reasoning, agentic coding, and large-scale knowledge workflows. It is the world's first open 3T-class model, featuring 2.8T total parameters with 104B activated, built on a 93-layer architecture with Kimi Delta Attention (KDA), Gated MLA, and Stable LatentMoE. The model uses a 7,168 hidden size, 96 attention heads, and 896 routed experts, activating 16 experts per token alongside 2 shared experts. Powered by MoonViT-V2 for native vision understanding and supporting a 1M-token context window, Kimi K3 is optimized for multimodal reasoning, long-context coding, advanced agentic workflows, and frontier-scale research applications

Deploy with AMD MI355XContact Sales

About this model

PaperBlogHF Model Card

Kimi K3 is a frontier-scale native multimodal Mixture-of-Experts model designed for long-horizon reasoning, agentic coding, and large-scale knowledge workflows. It is the world's first open 3T-class model, featuring 2.8T total parameters with 104B activated, built on a 93-layer architecture with Kimi Delta Attention (KDA), Gated MLA, and Stable LatentMoE. The model uses a 7,168 hidden size, 96 attention heads, and 896 routed experts, activating 16 experts per token alongside 2 shared experts. Powered by MoonViT-V2 for native vision understanding and supporting a 1M-token context window, Kimi K3 is optimized for multimodal reasoning, long-context coding, advanced agentic workflows, and frontier-scale research applications

Model Type

Vision-Language Model

Released

July 27, 2026

License: Kimi-K3

Parameters

2.8T

Model ID
moonshotai/Kimi-K3
Capabilities
Text GenerationInstruction FollowingReasoningMathematical ReasoningCode Generation+5

Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (moonshotai/Kimi-K3). Released under Kimi-K3. Further reading: Paper · Blog

Deploy Private Inference Endpoint

Choose your hardware and inference engine to get deployment commands and performance benchmarks tailored to your infrastructure

Hardware

MI355X

2,304 GB

Engine

vLLM
SGLang

Deployment code

INFERENCE COMMAND
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Powered by Vultr AgentBeta

Requires the vllm/vllm-openai-rocm:kimi-k3 Docker image or a standard vLLM image version greater than v0.26.0.

Performance under load

12k9.2k6.9k4.6k2.3k0163264128256512Total Tokens / secConcurrent requests
Tokens/s (total)

Benchmarks measured by Vultr on MI355X · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.

SS

Shivam Sharma

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AMD Instinct MI355X

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