OpenAI just upgraded its GPT-6 models to tackle low-resource legacy languages like COBOL and Fortran. On the new MultiLangBench benchmark, GPT-6 Astra reached an 87.4% pass rate across 20 languages, while GPT-6.1 Sol hit 97.9% accuracy when migrating COBOL code to modern stacks at lower cost. Why it matters: Critical financial systems running on decades-old code can finally be modernized without terrifying rewrite risks.
OpenAI just increased the default context length for GPT-6.1 Sol in Codex and Work from 272k to 500k tokens, an 80% jump. The change helps minimize context compactions during long sessions and retains finer nuances over time. OpenAI calls 500k the tested sweet spot for most workflows, though users can still manually override it up to the model's 1M maximum limit.
OpenAI just launched an Ultrafast mode for its GPT-6.1 Sol model, running up to 8x faster than standard speeds while keeping near-Astra intelligence. Designed for live experiences, outage triage, and app-navigating agents, it hits the API at $12/$60 per million tokens and rolls into Codex and ChatGPT Work for eligible high-tier accounts.
OpenAI just boosted the default inference speed for GPT-6 Astra and GPT-6.1 Sol by around 50%, pushing output from 30 to 50 tokens per second. The rollout applies across all subscription tiers and partner apps like Devin and OpenCode, kicking off a promised 28-day streak of daily shipping.
OpenAI just released GPT-6.1 Sol, an upgraded model delivering near-Astra performance on agentic coding and multi-step workflows at one-fifth the API cost. Standard pricing sits at $2 per million input tokens and $10 per million output tokens, with cached input cut to $0.10. It is available now in ChatGPT Work and Codex, with an Ultrafast version coming soon.
