GPT-6.1 Terra and Kimi K3.1 Pro launch, Cursor adds Computer Use, Codex CLI 0.164.0 adds /presets

tibo started a 28-day challenge at 05:33 KST on October 5. The promise: every day, ship one clear improvement that matters to most Codex and Work users, or do a full reset. His Day 22 post went up at 04:24 KST on October 27 and reads only "Day 22/ Terra is back!" Codex CLI 0.164.0 came out at 13:48 KST on October 23.

• The Day 19 post went up at 08:12 KST on October 24. Calls connect much faster for dots, and changing reasoning mid conversation no longer invalidates the cache.
• In a follow-up post, tibo said CLI usage has doubled since devday.
• /presets stores repeated prompts and slash commands in ten numbered slots and opens from the Ctrl+X P menu. /model and /permissions take the model, reasoning effort, speed and permission profile as arguments. The fullscreen transcript previews images on Kitty and Sixel terminals.
• Enterprise MCP sign-in works through Codex account grants or a dedicated sign-in, and it supports OAuth clients that need secrets. Remote Bash and Zsh snapshot sessions mask credentials, and the Amazon Bedrock setup wizard is now on by default.
• A failed compaction no longer leaves a partial summary, and resume finds compressed histories and restores thread settings. Windows proxy authentication works over HTTPS and WebSocket through Negotiate and NTLM. Config overrides passed with -c survive across subcommand levels, queued prompts wait for pending permission choices, and the macOS sandbox is hardened.
• Felipe Coury, who works on Codex CLI (X @fcoury), posted a demo of recalling a preset with Ctrl+X P in a review and fix loop. I found no independent real-use post.
• The version number 0.164.0 does not appear in tibo's Day 19 post. I treated the release notes as the same update because the timing and the features match.

Source: Codex 0.164.0 release notes ↗

Cursor announced Computer Use on its official X account at 00:59 KST on October 24. Agents click and type to drive apps on your computer, and Cursor uses it on its own when a task needs it. Update Cursor to try it.

• It also runs in the Windows app. A Cursor forum bug report from October 24 describes Computer Use permissions in the Windows app.
• Self-hosted workers have to opt in with agent worker --computer-use start. On macOS, a helper app called "Cursor Computer Use" needs Accessibility and Screen Recording permission.
• CLI v2026.10.22 adds agent env deploy --env <id>, which updates an existing Cloud Agent environment. Self-hosted workers register under the team you picked at agent login or agent team switch.
• A custom subagent pinned to a blocked, Max-only or unavailable model runs on the parent agent's model and notes which model it ran on. Composer 2.5 subagents run and bill at standard speed instead of the fast tier.
• Nested AGENTS.md files and always-apply rules apply when the agent edits or creates a file in a subdirectory. Compile caching and lazy initialization cut warm boot time by about 10%.
• X @qi9098 asked each agent to add a favorites feature to Cursor's official demo app and click through it in the iOS Simulator. With the same prompt, Codex with gpt-6-astra high took 2 minutes 1 second, Codex with gpt-6.1-sol high took 2 minutes 8 seconds, and Cursor with Grok 4.7 High took 8 minutes 17 seconds. He said Cursor spent over three minutes stuck on the All and Favorites toggle above the list.
• I could not find a separate blog post or changelog entry from Cursor for the desktop launch.

Source: Cursor announcement on X ↗

OpenAI released GPT-6.1 Terra at about 03:00 KST on October 27. Plus, Pro, Enterprise and Edu plans can use it in ChatGPT Work and Codex, and GitHub Copilot made it generally available at 04:15 KST. At max reasoning effort it scores below Sol on Terminal-Bench 4.0 and above Sol on Agents' Last Exam.

• On Terminal-Bench 4.0, Terra scores 24.8 at Low, 35.8 at Medium, 41.8 at High, 46.4 at Xhigh and 50.3 at Max, while Sol scores 47.1, 52.7, 53.0, 53.4 and 55.9. At every reasoning effort, Terra scores below Sol at the same effort, and Terra at xhigh, 46.4, is below even Sol at low, 47.1.
• OpenAI's model guide says Terra is "for everyday writing and visual work", Astra is "for the hardest end-to-end work", and Sol is "for repeated, long-running work". OpenAI says GPT-6.1 Sol and GPT-6 Astra remain the better choice for the most complex coding tasks.
• The API model name is gpt-6.1-terra. Context is 1,050,000 tokens, with up to 922,000 input tokens and 128,000 output tokens. In Copilot it sits in the Versatile tier, and GitHub describes it as built for "everyday agentic coding and terminal work".
• In his Day 22 post, tibo called it significantly better at writing, personality and nuanced understanding of requests, very good at computer use, and said it gives 2X more usage than 6.1 Sol across API and subscriptions. I could not confirm the 2X claim in OpenAI's announcement.
• On the Artificial Analysis Intelligence Index, Terra scores 48.11, Sol 51.83 and Astra 52.67. To run the index, Terra wrote 128,152,739 output tokens and Sol wrote 67,198,855, so Terra wrote about 1.9 times as many. On Coding Agent Index v2.0, Terra scores 48, Sol 54 and Luna 31.
• On the AA-Omniscience hallucination rate, lower is better. Terra scores 38.04%, below Sol's 54.27% and Astra's 51.34%, and below the previous generation GPT-5.6 Terra's 87.88%. Of the models compared, only Gemini 4 Argon at 15.07% and Grok 4.7 at 29.34% score lower.
• Some use it as a subagent under Sol. X @adidoit said that after an hour it barely touched his quota and computer use got better.
• Computer use is fast. X @victornunez had both models fill the same long form in Fast mode, and Terra took 53.5 seconds against Sol's 3 minutes 21.7 seconds.
• X @taylorhbuilds ran Codex 150 times on his own code. Median time was 29 seconds for Terra High and 87 seconds for Sol Medium, and Sol had 9 more accepted runs out of 50. He uses Terra for quick work and Sol when it has to be right, and still does not know where to use Terra.
• A Plus user on Reddit r/codex said that on the same project Terra max used 33% of the 5-hour limit in 18 minutes, while Sol medium used 24% in about 30 minutes. It is one person's test and it conflicts with the 2X usage claim.
• Other r/codex posters called it lazy, saying it finishes early and admits it skipped the work when you point it out, or a weird middle child, saying they mix Luna and Sol and do not see why Terra needs to exist.
• On HN, OpenAI employee tedsanders called Terra a midrange API option with fast computer use and possibly strong technical communication. He said it does not replace both Sol and Astra.

Source: OpenAI announcement ↗

Moonshot opened Kimi K3.1 Pro and Kimi K3.1 Pro Highspeed on October 23, US time. The context window is 1M tokens, and Kimi Enterprise admins have to turn the model on. In Moonshot's table, Terminal-Bench 4.0 is 65.7, 0.7 points below Claude Opus 5.5's 66.4.

• Moonshot says K3.1 Pro is a post-trained version of K3 that used substantially more post-training compute. It runs on Kimi.ai, the Kimi mobile apps, Kimi Work, Kimi Code and the Kimi API, and input is text and images.
• The two sources give different sizes. Moonshot says 3T-class, and Artificial Analysis lists 2.8T total with 104B active.
• Moonshot promised the weights by November 4, 2026. As of October 27, 2026, they are not published.
• Highspeed is officially 2 to 3 times faster. AIHubMix measured 1.6 to 1.75 times, and 85 to 90% of the tokens were reasoning tokens.
• Artificial Analysis gives an Intelligence Index score of 55, fourth place, and 1,846 Elo on GDPval-AA, third place. Its own Terminal-Bench 4.0 run gives 67%, the highest of any model it has measured, against 64% for Claude Sonnet 5.5 and 13% for K3. That differs from Moonshot's 65.7 because a different party ran it, and it is unknown whether the harness and setup were the same.
• The AA-Omniscience hallucination rate fell from 53.20% for K3 to 43.89%, and AutomationBench-AA rose from 58% to 73%. Moonshot's internal Hallu Bench Hard claim-level rate fell from 23.4% for K3 to 8.3% for K3.1.
• The Hacker News thread went up at 01:59 KST on October 24 and drew 1,089 points and 655 comments. Commenters said cyber-related data was removed from the open weights and that cyber capability was held down on purpose (TuxSH, rudolftheone), and one said Terminal-Bench 4 is close to saturated (Tiberium).
• simonw said Moonshot's creator campaign docs help you spot paid boosters, and taytus complained about usage limits.
• X @ValgoDev gave the same three.js lighthouse prompt to three agents. Kimi took 5.6 minutes, Codex 8.8 minutes and Claude Code 17.3 minutes, and he said Claude's result was best and Kimi's was too dark to see.
• X @PovilasKorop ran K3.1 Pro at MAX level. It scored higher than High and ran 2.5 times slower, and he hit 429 errors a few times when Kimi's servers were full.

Source: Kimi K3.1 Pro official blog ↗