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one cloud for compute, inference, and agents Question: https://teapawt.net/t.co/dOcscX4hmx Japan: @gmicloudJapan

Mountain View, CA
Joined December 2023
Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)Photo by GMI Cloud (@gmi_cloud)
Our 2 takes on @ArtificialAnlys Intelligence Index v5: 1. 60% of the score now comes from private test data. Harder for models to train with the test data. 2. The median frontier model now uses 59k output tokens per task, from 35k. that means infra needs predictable throughput and cost to keep up with longer, multi-step runs. more 👇
Announcing Artificial Analysis Intelligence Index v5, featuring 2 new benchmarks and 3 upgrades. For the first time, the majority of the Index is built on private datasets The Artificial Analysis Intelligence Index is our composite measure of model capabilities across tasks reflecting real-world usage today. v5 is our biggest upgrade since v4 launched in January. With v5, 60% of the Index is now based on evaluations with private test sets or held-out answers. Alongside Intelligence Index v5, we’re launching the Artificial Analysis Progress Index v1, which tracks model capability over time on one continuous scale. New to the Intelligence Index: ➤ FrontierCode 2.0: Cognition's newly-launched private benchmark of real-world coding tasks, graded on whether a repository maintainer would merge the agent's change ➤ Terminal-Bench-Science: 70 agentic scientific research tasks, run in a terminal environment Upgraded: ➤ HLE-Diamond (replacing Humanity's Last Exam): a refined 1,000-question version of Humanity's Last Exam, split evenly between reasoning and knowledge questions ➤ AA-Omniscience v1.1: An updated dataset with saturated and public set questions removed, new questions added, and ambiguous or erroneous questions revised ➤ CritPt v2: a private, 40-question hard subset of CritPt v2, revised by the CritPt authors and run with a code-execution tool Staying in the Index: AA-Briefcase, AutomationBench-AA, GDP.pdf and Terminal-Bench 4.0 Removed from the Index: GDPval-AA v2.1, SciCode, and AA-LCR v1.1 Key results: ➤ Claude Opus 5.5 (max) leads at 58, ahead of GPT-6 Astra (max, 57) and GPT-6.1 Sol (max, 55): Anthropic and OpenAI hold the top five models. Gemini 4 Argon (high) is next at 50 ➤ The open weights gap widens from 3 points to 12: Kimi K3.1 Pro (weights not yet released) is the top open weights model at 46. Among released weights, DeepSeek V4.1 Flash 1017 (max) and GLM-5.3 (max) lead at 32 - 26 points behind the leader and below Claude Haiku 5.5 (max, 36) ➤ Cost per task varies by more than 13x among the leading models: of the 10 highest-scoring models shown, GPT-6.1 Terra (max) is the cheapest at $0.96 per Intelligence Index task and Claude Fable 5.1 (max) the most expensive at $13.04
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9 new Clouders are joining our Clouder community! Meet our newest members and connect with them here: @SyedMuz09713276, @insomnia_vip, @Dhirender_0001, @jiayuliiop8, @Lycellia_J, @Manan__Agrawal, @NURM_Dima, @laziedev We've also revamped our Clouder Rewards Program to better recognize and reward the incredible work our community is building with us 🙏 And we're still growing! Join us here 👇
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Tested Kimi K3.1 Pro and Claude Opus 5.5 on the same prompt: creating a beautiful, highly detailed Japanese pixel-art street corner. Kimi K3.1 Pro is a cheaper alternative, though it’s not at Opus 5.5 quality yet.
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One more discount till November 1! Get 15% off MiMo V2.6 Flash on GMI Cloud now👇
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GMI is now a built in provider in @kilocode use 300+ models from GMI on Kilo Code without any setup
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That's a wrap on Spooky Demo Day. 🎃 6 weeks of building on @gmi_cloud + @nvidia. 110 builders and investors. One amazing night at @agihouse_org. Thank you so much to our Cohort 2 teams, mentors, partners, and everyone who came out! Already can't wait for Cohort 3 this spring 👀
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The week in numbers. gmi started on Sat 17 Oct and shipped 1.0 on Sun 25 Oct. 92 commits up to the release. 296 offline tests. 93 GMI API operations as commands. 36 MCP tools by default, 78 with writes on and 90 with deletes on.
Final day of @zkasuran x GMI: gmi 1.0.0 is out. One line installs it: curl -fsSL raw.githubusercontent.com/zk… | sh Chat, images, video, all 93 GMI API operations, sandboxes and an MCP server for agents. Apache-2.0. github.com/zkasuran/gmi
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What is not proven: the Claude Code and Cursor MCP setups have not been run. gmi serve runs from a Docker image locally but is not on the AgentBox marketplace yet. macOS and Windows are untested.
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Seven issues are open and six are marked good first issue. Try the installer on macOS or Windows, verify the Claude Code or Cursor setup, or add fake-server tests for media. github.com/zkasuran/gmi/issu…
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Final day of @zkasuran x GMI: gmi 1.0.0 is out. One line installs it: curl -fsSL raw.githubusercontent.com/zk… | sh Chat, images, video, all 93 GMI API operations, sandboxes and an MCP server for agents. Apache-2.0. github.com/zkasuran/gmi
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Just a Normal Night. Probably.|今晚一切正常,大概吧! 🐕 帶狗狗出去散個步,應該不會遇到什麼怪事吧? 除了天上有眼睛, 路邊有奇怪的生物, 還有整座城市看起來都不太正常…… 嗯,至少狗狗很淡定。😂 🐾 Just taking the dog for a walk. What could possibly go wrong? Floating eyes? Check. Strange creatures? Check. An entire city acting suspiciously? Also check. Well, at least the dog's having a good time. @gmi_cloud #GMI #Seedance #Midjourney #AIAnimation #AIShorts
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What the agent may do. By default gmi mcp serve exposes 36 read tools.   --allow-write adds 42 write tools. --allow-destructive adds 12 delete tools. Sandbox tokens and API key creation are never exposed. Tool output is redacted and capped.
Day 5 of @zkasuran x GMI: gmi mcp serve gives an agent GMI Cloud as tools. Here Codex, running gpt-6.1-sol, starts a sandbox, runs a command, asks a model about the result and builds a template. Hands off the keyboard.   AMA: @zkasuran answers in the replies
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Day 5 of @zkasuran x GMI: gmi mcp serve gives an agent GMI Cloud as tools. Here Codex, running gpt-6.1-sol, starts a sandbox, runs a command, asks a model about the result and builds a template. Hands off the keyboard.   AMA: @zkasuran answers in the replies
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we asked kimi k3.1 pro @Kimi_Moonshot to create an aquarium of creatures from the cthulhu mythos ran it for 4h30m and cost about $39 we wanted to push it further, but it had a hard time realizing the details
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