Kimi K2.7 Code vs GLM 5.2: Specs, Pricing & Which to Choose (2026)
Kimi K2.7 Code vs GLM 5.2 compared: specs, API pricing, context window, VRAM and a clear verdict on which model to choose in 2026.
Older stories and guides from the Convly archive.
Kimi K2.7 Code vs GLM 5.2 compared: specs, API pricing, context window, VRAM and a clear verdict on which model to choose in 2026.
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Claude Opus 4.8 vs GPT-5.5 compared: specs, API pricing, context window, VRAM and a clear verdict on which model to choose in 2026.
We combined live API pricing with the Artificial Analysis Intelligence Index to rank AI models by intelligence per dollar. The price spread is 114× — but value tells a very different story.
NVIDIA’s Nemotron 3 Nano Omni packs vision, audio, video, and text into one open 30B-A3B model with only 3B active parameters. Here’s what it does, how good it is, and what it takes to run.
Moonshot’s Kimi K2.7 Code is a 1T-parameter open-weight model built only for agentic coding. We verify the specs, the vendor benchmarks, the int4 hardware reality, and whether its aggressive $0.95/$4.00 pricing actually beats the closed frontier.
Huawei has turned its AI silicon plans into a dated, one-chip-a-year roadmap, opened the openPangu 2.0 models, and committed to open-sourcing CANN. We weigh all of it against the constraints the keynote skipped: a 7nm ceiling at SMIC, a homegrown HBM supply that can feed only a few hundred thousand chips, and a per-chip gap to NVIDIA that Huawei’s own roadmap admits.