KIMI K2.6
Released April 2026. Multimodal. Agentic 1T-parameter MoE architecture. 256K-token context. Strong at long-horizon coding and multi-agent orchestration. $0.60/$2.80 per million tokens.
Kimi K2.6 is Moonshot AI's flagship as of April 2026 — a 1-trillion-parameter Mixture-of-Experts model engineered specifically for agentic workloads. It pairs a 256K-token context window with vision input and a training regime tuned for long-horizon code editing and multi-agent orchestration. Pricing lands at $0.60 per million input tokens and $2.80 per million output, putting it between budget Grok models and the OpenAI / Anthropic flagships. The case for Kimi K2.6: agentic coding pipelines that need to plan-act-observe over many steps without losing the plot, multi-agent setups where you want one model that's actually trained for tool use and self-coordination, and Chinese-language work where Moonshot is the natural strong choice. The case against: the tool-calling ecosystem outside of agent frameworks is less mature than OpenAI's, and for one-shot reasoning prompts GPT-5.5 or Claude Opus 4.7 still produce a cleaner answer. On Council AI, Kimi K2.6 is routed through OpenRouter rather than a dedicated Moonshot provider — set OPENROUTER_API_KEY in your environment.
Moonshot trained K2.6 on long sequences of plan-act-observe loops rather than just one-shot prompts. That makes it materially better at maintaining a goal across many tool calls — the failure mode where models 'forget the plan' shows up less often.
$0.60 per million input tokens and $2.80 per million output tokens. Council AI bundles it inside monthly plan budgets.
Council AI doesn't ship a dedicated Moonshot provider — Kimi requests go through OpenRouter, which adds a small latency hop but keeps integration simple. Set OPENROUTER_API_KEY in your environment if you self-host.
One trillion total parameters in a Mixture-of-Experts architecture, where only a fraction of those parameters activate on any given token. That's how Kimi gets flagship-tier quality at mid-tier prices.
Yes — text and image input. Useful for agent flows that need to read screenshots, diagrams, or UI mockups mid-loop.
For single-prompt code edits or refactors, Sonnet 4.6 still wins on patch quality. For long-running agentic coding sessions where the model has to plan over many steps, Kimi K2.6 is the more interesting pick.
Not natively. If you need fresh information, pair it with a search tool in your agent loop, or use Grok 4.3 / Gemini 3 Pro instead.