Kimi K2.6 Now Available for Telnyx AI Assistants

Telnyx has made Moonshot AI's Kimi K2.6 model available for AI Assistants in the US region, offering developers on-network inference to reduce latency and simplify infrastructure. The model scores 58.6 on SWE-Bench Pro and 80.2% on SWE-Bench Verified, outperforming GPT-5.4 on coding benchmarks while using only 32 billion active parameters per token for cost efficiency.

Contact us https://telnyx.com/contact-us Log in https://portal.telnyx.com 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. 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. 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 .