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Articles, guides, and insights on local artificial intelligence
3 articles found per "ollama"
MiniCPM-V 4.7: the 35B MoE that runs on a smartphone with 3 GB of RAM
MiniCPM-V 4.7 (35B total, ~3B active, released October 12, 2026 by OpenBMB and ModelBest) is the first open MoE in the series, vision-language: multiple images, video, OCR. 13+ tok/s with 3 GB of RAM on an iPhone 17 Pro Max, 17+ on Android. Official quantizations BF16, FP8, INT4, AWQ, GPTQ, GGUF; engines Ollama, llama.cpp, vLLM, SGLang. The three techniques: Lookahead Expert Scheduling, fine per-level quantization, DSpark speculative sampling.
Aleph Alpha's Kolibri: the 78B MoE that runs (almost) locally
Aleph Alpha's Kolibri (78.1B/3.46B, Apache 2.0, FP8) is the European open-weight MoE: reasoning, tool calling and context up to 1M tokens. In FP8 it weighs ~78GB of VRAM: it runs on an RTX 5090 32GB + shared RAM or on unified-memory Macs; for practical adoption the kolibri1 architecture in llama.cpp and Ollama/LM Studio builds are still missing.
Qwen: the open model with the best multilingual support
Qwen is the open family with the best support for Italian and French: generations, sizes, MoE, when to use it, and a quick comparison with Llama.