GPT-6.1 Terra just dropped and OpenAI is already telling you NOT to use it for the hard stuff.
Their own announcement says:
For the most complex coding tasks → stick with Sol or Astra.
Terminal-Bench score at max effort → only 50.3%.
Factual error rate at max reasoning → still 4.3%.
Cybersecurity rating → still just “Critical.”
So they shipped a cheaper, faster model… and then immediately told everyone the expensive ones are still better when it actually matters.
GPT-6.1 Terra is Live:
OpenAI just made its model pricing a lot more interesting.
GPT-6.1 Terra: $2/$10
GPT-6.1 Sol: $4/$20
GPT-6 Astra: $20/$100
Terra is HALF the price of Sol and 10x cheaper than Astra at Fast speed.
It also lists a 1M+ context window.
GPT-6.1 Terra: delivering fast and capable computer use at a lower price.
GPT-6.1 Terra understands what’s on screen, takes action across apps, writes naturally, and is a more capable model for your whole workday with the efficiency to take on more of it.
Which AI coding subscription actually gives you the best value for money in October 2026??
• Codex Plus ($20) → Access to Astra & 6.1 Sol
• Claude Pro ($20) → Opus 5.5 & Sonnet 5.5
• Google AI Pro ($20) → Gemini 4 Argon + Flash
• Cursor Premium ($30) → Only includes Grok 4.7 & Composer 2.5 in the weekly pool (Claude & GPT bill extra at raw API rates)
If you could only keep ONE $20 subscription for the rest of the year, which one survives??
GPT-6.1 Terra Fast speed pricing
At Fast speed, it costs $2 input / $10 output per million tokens.
That's HALF the price of GPT-6.1 Sol ($4/$20) and 10x cheaper than GPT-6 Astra ($20/$100).
And Terra comes with a 1M+ context window.
GPT-6.1 Terra pricing:
• $1 input / $5 output per million tokens
• 1.05M context window
• 128K max output
• Fast, with highest-tier reasoning
• Text and image input
GPT-6.1 Terra pricing:
• $1 input / $5 output per million tokens
• 1.05M context window
• 128K max output
• Fast, with highest-tier reasoning
• Text and image input
This is SHOCKING.
Cohere caught Alibaba's Qwen AI model attempting to send data to a server in Beijing during a cybersecurity test.
Its reasoning trace indicated no tool use. Its actions told a different story.
The sandbox blocked the upload. The cause remains unknown.
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected.
Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions.
Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent.
But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models?
We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem.
Read the full report: https://t.co/TZSugXi2ZE
🚨BREAKING: Microsoft is offering 60,000 employees BUY OUT.
More than 1 in 4 workers are eligible for voluntary buyouts across the US, UK, Canada and India.
As Microsoft pours billions into AI infrastructure, it's offering thousands of employees money to leave.