--- title: Kimi K2.6 Now Available for Telnyx AI Assistants canonical: https://telnyx.com/release-notes/kimi-k2-6-ai-assistants --- # Kimi K2.6 Now Available for Telnyx AI Assistants [Release notes](https://telnyx.com/release-notes) # Kimi K2.6 Now Available for Telnyx AI Assistants ### 11, Jun 2026 Kimi K2.6 by Moonshot AI is now available as a model option for Telnyx AI Assistants in the US region. Developers can select moonshotai/kimi-k2-6 directly in Mission Control or via the Assistants API, with inference running on Telnyx-hosted infrastructure alongside STT, TTS, and telephony in a single system. ### What is new * **Kimi K2.6 agentic model:** Select moonshotai/kimi-k2-6 as the LLM for any AI Assistant, with no separate API integration or vendor contract required. * **1T MoE with 32B active parameters:** Kimi K2.6 uses a Mixture-of-Experts architecture that activates 32 billion of its 1 trillion total parameters per token, delivering frontier-level quality at a fraction of the compute cost of a dense model of equivalent size. * **256K context window:** Process up to 262,144 tokens in a single request, enough to ingest large codebases, legal documents, or extended conversation histories without chunking or summarization. * **Native multimodal input:** The integrated MoonViT vision encoder accepts image inputs alongside text, enabling assistants that can read screenshots, diagrams, and documents as part of their reasoning. * **Agent swarm orchestration:** K2.6 supports coordinated workflows across up to 300 parallel sub-agents and 4,000 tool-calling steps, making it suited for complex multi-step tasks. * **US region availability:** Inference runs on Telnyx-hosted compute in the US, keeping the full pipeline on the same private backbone. ### Why it matters Kimi K2.6 scores 58.6 on SWE-Bench Pro and 80.2% on SWE-Bench Verified, outperforming GPT-5.4 on real-world coding benchmarks and matching frontier models on agentic tasks. For developers building AI Assistants that need to reason through multi-step workflows, debug code, or coordinate tool calls across long horizons, this is a model purpose-built for that workload. Running K2.6 on Telnyx infrastructure means the LLM call never leaves the private backbone. In a voice AI pipeline, every vendor boundary adds 30 to 80ms of latency. On-network inference eliminates that hop entirely, and removes a separate API key, vendor contract, and billing relationship. One system handles telephony, transcription, inference, and synthesis. The MoE architecture also makes K2.6 cost-efficient at scale. Only 32 billion parameters activate per token, so you get the quality of a trillion-parameter model without the inference cost of one. ### Example use cases * Engineering teams building voice assistants that can walk users through complex debugging or code-generation workflows across large codebases, using the 256K context window to maintain full project context. * Customer support operations deploying agents that reason through multi-step troubleshooting, using K2.6's tool-calling capabilities to query databases, look up order details, and execute remediation steps autonomously. * Product teams creating assistants that process visual inputs (screenshots, UI mockups, scanned documents) alongside text prompts to provide contextual guidance. ### Getting started 1. Navigate to Mission Control, then AI, then Assistants. 2. Create a new assistant or select an existing one. 3. In the assistant configuration, select Kimi K2.6 from the model dropdown. 4. Save and test your assistant. **Learn more** in the [AI Assistants documentation](https://developers.telnyx.com/docs/inference/ai-assistants) or the [Kimi K2.6 model card](https://huggingface.co/moonshotai/Kimi-K2.6). 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