Kimi K2.7 Code: 1T MoE, $0.95/M tokens, MIT license, beats Opus 4.8 on MCP tool-calling

Reddit r/AI_Agents Models
coding open-weights mixture-of-experts moe huggingface api tool-calling

Summary

Moonshot AI 发布了专注于编程的开放式权重模型 Kimi K2.7 Code，拥有1万亿参数和384个专家，性能在MCP工具调用上超越Opus 4.8，成本仅为十分之一。

Moonshot AI released Kimi K2.7 Code on June 12 — a coding-focused open-weight model. Key specs: \- 1 trillion params (MoE, 32B active, 384 experts) \- 256K context window \- Modified MIT license — weights on Hugging Face \- $0.95/M input, $4.00/M output via Kimi API \- Works with Claude Code, Cursor, OpenCode, OpenRouter Benchmarks (vendor-reported, independent pending): \- MCP Mark Verified: 81.1% (Opus 4.8: 76.4%) \- Kimi Code Bench v2: 62.0 (Opus: 67.4, GPT-5.5: 69.0) \- 30% fewer reasoning tokens than K2.6 Not a Fable 5 replacement (Fable scored 80% on SWE-Bench Pro). But at 10x less cost with open weights — different value proposition entirely. Especially now that Fable is banned. Anyone self-hosting this yet? Curious about real-world latency on consumer hardware.
Original Article

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