Fireworks Turns Kimi K3 Into Ember-1, Cuts Tokens 40%
Fireworks AI post-trains Moonshot's open Kimi K3 into Ember-1, cutting output tokens by about 40% while matching coding scores, at the same per-token price.
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Fireworks AI post-trains Moonshot's open Kimi K3 into Ember-1, cutting output tokens by about 40% while matching coding scores, at the same per-token price.
Inferact's open-source megakernel lets 16 Google TPU v7 chips decode Kimi K3 57% faster than 16 Nvidia GB200 chips, even though GB200 leads on paper specs.
Moonshot AI launched Kimi Code Desktop on Sept 21 with a GUI for its coding agent, while a Sept 18 hands-on piece revealed model and pricing details the launch post left out.
Moonshot AI swapped Kimi Code to K2.8 Preview under the same model ID, adding 1M-token context for all tiers and revising permission rules for risky commands.
Model choice, Azure hosting and coding-model price pressure.
Moonshot AI released Kimi K2.7-Code with a HighSpeed mode, strong self-reported tool-use scores and a much lower output price than Claude Opus 4.8.
Moonshot AI used a cluster of Kimi agents to simulate all 104 matches and identify probability gaps, including a higher chance for Germany than betting markets imply.
Moonshot's open MoE model offers far cheaper input and output tokens while improving agent-style coding benchmarks over K2.6.
Moonshot's desktop agent runs on local files, logged-in browsers and scheduled tasks, targeting users who cannot move sensitive data to the cloud.
Moonshot open-sources Kimi K2.7-Code for AI coding.
Kimi’s maker is reportedly raising $2 billion after ARR doubled from March to April and its K2 line moved from chat toward agents.
Moonshot AI is already discussing another round that could lift its valuation from $20 billion to $30 billion, with Kimi turning open-source model performance into a financing story.
Nvidia unveiled Nemotron 3 Ultra, a 550-billion-parameter open-source model, but it scored 48 on the Artificial Analysis intelligence index, behind Kimi K2.6's 54.
Meituan-backed investors have pushed Kimi maker Moonshot AI to a $20 billion valuation, testing how far China's model-company pricing can run.
Moonshot AI has raised $2 billion at a $20 billion-plus valuation, putting Kimi at the center of China’s race for open-source large models and a possible Hong Kong listing.
Moonshot AI released the full production-grade Kimi K2.6 model, which scored 54.0 on HLE-Full, surpassing closed-source models Claude Opus 4.6 and GPT-5.4. The 1-trillion-parameter MoE model activates only 32B parameters per inference and supports up to 300 parallel sub-agents.
Moonshot AI has rolled out the K2.6 code preview to all Kimi Code subscribers, offering deeper reasoning chains, improved multi-step agent planning, and more reliable tool calls at a fraction of the cost of competing models.
Cursor's new Composer 2 model is built on Moonshot AI's open-source Kimi K2.5, a fact the company initially omitted from its launch materials. The revelation has sparked debate about transparency in AI development.
Moonshot AI open-sourced the trillion-parameter Kimi K2 MoE model, activating only 32B parameters per token, with strong coding and agent performance.
Moonshot AI's Kimi K2.5 introduces native multimodal understanding and an Agent Swarm feature that splits complex tasks into parallel sub-tasks handled by multiple agents, significantly boosting speed.
Moonshot AI's K1.5 model, released before K2, demonstrates that pure reinforcement learning can enhance reasoning capabilities, validating the approach for scaling to larger models.