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// 64d agoMODEL RELEASE
Kimi K2.5 sparks local-run debate
The thread is a reality check on Moonshot AI's Kimi K2.5: it looks strong on paper, but running it locally still means serious hardware or aggressive quantization. It quickly turns into a comparison with GLM-5 and smaller open models that may be easier to host.
// ANALYSIS
Kimi K2.5 is not the universal best, but it is the most interesting open model if your workload is visual and agentic. For pure text coding, GLM-5 looks like the more practical challenger.
- –K2.5's moat is multimodality plus orchestration, not just raw size.
- –Local use is the catch: even useful quants want roughly 240GB of combined RAM/VRAM, and the full model sits in datacenter territory.
- –GLM-5 is text-only, and its self-reported tables edge K2.5 on some text-heavy coding and terminal tasks, but K2.5 keeps the multimodal lead.
- –My read is that Qwen3.5 or MiniMax-M2.5 are the lower-footprint compromise picks, but they trade away K2.5's visual and swarm features.
- –Community feedback stays split between K2.5's front-end strength and GLM-5's more practical text-first performance.
// TAGS
kimi-k2-5glm-5llmopen-sourcemultimodalagentai-codingself-hosted
DISCOVERED
64d ago
2026-03-24
PUBLISHED
64d ago
2026-03-24
RELEVANCE
9/ 10
AUTHOR
Felix_455-788