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Meta Muse Glimmer Is Out: 30B, Apache 2.0, and Deployable on Swfte Immediately
Meta's 29.6B dense multimodal model fits in 24GB. Architecture, memory math, and the case for narrow models.
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Meta Muse Glimmer Is Out: 30B, Apache 2.0, and Deployable on Swfte Immediately
Meta's 29.6B dense multimodal model fits in 24GB. Architecture, memory math, and the case for narrow models.
AI Image and Video Models in 2026: A Buyer Comparison With Real Per-Shot Costs
Veo 3.1, Kling 3.0, Seedance and Flux 2 compared on price, licensing and cost per usable shot.
Qwen3.8-27B: The Version You Can Actually Run, and How to Prepare For It
Qwen3.8-27B is the checkpoint that fits one GPU. What is confirmed, what is not, and the VRAM maths.
Qwen3.8-Max: Alibaba Ships 2.4 Trillion Parameters, With Open Weights Promised
Qwen3.8-Max launched at $2/$6 per million tokens. What is verified, what is vendor claim, and what is missing.
How Cheap Is DeepSeek, Really? A Cost Comparison Against Every Leading Model
DeepSeek V4-Pro costs $0.435/$0.87 per million tokens. The real multiple against GPT-5.6, Fable 5 and Gemini.
Where Token Prices Are Going: What to Budget for LLM Costs Through 2027
LLM token prices keep falling while AI bills keep rising. The four forces driving each, and how to budget for both.
Build Your Own AI on Your Own Data: Open Source Stack or Managed Platform
Training AI on your company data in 2026: the open source toolchain compared against a managed path.
LLM Model Distillation Explained: Why Distillation-as-a-Service Is the Missing Layer
Distillation turns a model nobody can run into one anyone can. The mechanics, economics, and why we explore it.
How to Fine-Tune an LLM on Your Own Data (And Why the Moat Was Never the Model)
Prompt, retrieve, or fine-tune? A practical guide to training a specialised model on your own data in Swfte.
Kimi K3 Open Weights Are Out: Download, Self-Hosting Requirements, and What Changed
Moonshot shipped 2.8T parameters on schedule. Independent numbers, serving math, and why policy cannot undo it.
Project Alexandria: Our Open-Source AI Training Corpus and Distillation Pledge
Libraries burn; distributed ones do not. Our pledge to publish open distillations, a corpus, and what we learn.
How to Run a 27B LLM on Your Phone: Bonsai 27B, 1-Bit and Ternary Quantization
Bonsai 27B fits a 27B model in 3.9 GB. What survives 1-bit and ternary compression, and what quietly breaks.
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