In scope: quantization, mixture-of-experts, distillation, context handling, evals — and the specific-and-local cluster: fine-tuning, personalisation, open-weight releases, and running models on your own compute. Out: general AI research that moves neither cost nor capability per token, and the system around the model, which lives in harnesses.
| Type | Source | Published |
|---|---|---|
| ANALYSIS | DeepSeek V4 — Open-Weight Trillion-Parameter MoE at ~1/6th Frontier Cost VentureBeat (corroborated by morphllm.com + Hugging Face model card) · DeepSeek DeepSeek V4 (open-weight MIT): V4-Pro 1.6T/49B-active, V4-Flash 284B/13B-active, 1M context, ~$0.435/$0.87 per-Mtok — near-frontier capability (SWE-bench Verified ~80.6%, GPQA ~90–92%) at ~1/6th the cost of Opus 4.7 / GPT-5.5; lands inside an 8-day April-2026 frontier window. | 2026-04-24 |
| ANALYSIS | GPT-5.6 — OpenAI's Three-Tier (Sol / Terra / Luna) Frontier Family + Token-Efficiency Claims Tech Startups (corroborated by CryptoBriefing; OpenAI's own page returned HTTP 403) · OpenAI OpenAI launched GPT-5.6 as three tiers (Sol $5/$30, Terra $2.50/$15, Luna $1/$6 per Mtok) on 2026-07-09; claims 54% higher token efficiency on agentic coding vs rivals plus a 90% cached-read discount — a live instance of tier-differentiated frontier pricing. | 2026-07-09 |