Introducing Kimi K3 on DeepInfra - Deep Infra

DeepInfra has introduced Moonshot AI’s Kimi K3, an open-weight sparse Mixture-of-Experts model with 2.8 trillion total parameters but 104 billion activated per token, designed for long-horizon coding, agentic work, multimodal reasoning, and large-context applications. The model uses Kimi Delta Attention, Attention Residuals, and a Stable LatentMoE design that routes tokens across 16 of 896 experts, which Moonshot reports improves scaling efficiency over Kimi K2, while providing a native context window of roughly one million tokens and image and video support through the MoonViT-V2 encoder. DeepInfra reports strong benchmark results, including a leading 42.0 score on SWE-Marathon, while noting that K3 uses thinking mode by default, requires full assistant-message history in multi-turn tool workflows, and may need explicit constraints for autonomous agent tasks. Available through DeepInfra’s OpenAI-compatible API as moonshotai/Kimi-K3, it supports JSON output, function calling, and multimodal inputs, with usage-based token pricing, cache discounts, optional private deployments, and the provider’s stated zero-retention and security certifications.

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