Gemini 4 Carbon from @GoogleDeepMind is now live on OpenRouter, via @googlecloud.
Built for long-horizon agentic coding and cybersecurity. Google reports big gains over Gemini 4 Argon on exploiting vulnerabilities, agentic terminal tasks, and long-context reasoning.
Introductory pricing is 50% off through Nov 30: $2/M input and $10/M output.
Gemini 4 Carbon from @GoogleDeepMind is now live on OpenRouter, via @googlecloud.
Built for long-horizon agentic coding and cybersecurity. Google reports big gains over Gemini 4 Argon on exploiting vulnerabilities, agentic terminal tasks, and long-context reasoning.
Introductory pricing is 50% off through Nov 30: $2/M input and $10/M output.
Gemini 4 Carbon is rolling out today. Itโs built for sustained, long-horizon tasks, reasoning deeply through complex software engineering, cybersecurity, and scientific discovery.
Coming globally via the Gemini API in @GoogleAIStudio and Gemini for business, and for Ultra subscribers in @antigravity, the @GeminiApp, and AI Mode in Search.
Iโm curious to see how to bridge the remote gap. e.g. OpenClaw Multiplayer launched last week where teammates jump into the same live session. Radical transparency into what everyoneโs working on, or chaos.
Eitherway, excited to be here in person. If youโre at @aidotengineer this week, would love to say hi! ๐
I joined Google DeepMind ~2 months ago! In SF & MTV for @aidotengineer!
โAs a singleton in Singapore working on model launches & partners (team in EU/US), I learnt:
โ1. Async work is autoregressive - continuous tokens in/out
2. In-person is latent diffusion
3. Trust is an efficient protocol ๐งต
When building hard things:
1. Async feels autoregressive. You read a doc, reply to a chat, ship a PR. Itโs fast and linear, but you only attend to whatโs explicitly passed into your context window, even if itโs large.
2. In-person is latent diffusion. Overhearing a desk convo, wandering into a random talk, lunch chatter. Itโs noisy, but somehow I get a much better sense of what to actually attend to.
3. Quote @benoitschilling - the tech will change, so focus on the people. Trust is an efficient protocol.
our team uses gemini quite a bit now
whenever we have a tricky architectural problem, complex system design questions, or need to simplify something we ask for a gemini subagent
it's pretty good here. i don't see this talked about much
Introducing Gemini 4 Carbon, it's a big jump over Argon which we released just 2 weeks ago.
Gemini 4 Carbon is SOTA on cyber, long horizon tasks, ranks #1 on Artificial Analysis V5, significantly improves on usability in domains like coding, and is more aligned.
We launched the Gemini API CLI. A CLI for calling the Gemini API. Give it to the agent you already use (Claude Code, Codex, Antigravity, Cursor, OpenClaw, Hermes...). It's NOT a new coding agent you can use it too:
1. Generate images, video, speech, music.
2. Analyze PDFs, images, audio, video, YouTube URLs,
3. Transcribe recordings to md / json / srt,
4. Run Deep Research in the background.
Stateless. No memory, no chat mode. Your agent owns the context and the plan, gemini-api does the API call. Build for Agents, it's self-describing. `--help`, `--dry-run`...
Start here: https://t.co/D812RdijJO
Gemini 4 Argon Developer Guide ๐งโ๐ป
Here are a few tips when using Argon:
๐ฏ - Align on goals & intent upfront
๐งช - Give it a way to verify & test its work
๐ค - Have Argon delegate to Flash subagents
๐ - Update rules & skills
Read the full guide ๐
https://t.co/UJmmqBwVi5
Gemini 4 Argon had the best launch day user share of any frontier model on Cline since June.
~3x as many users tried it on day one as Claude Opus 5.5 or Sonnet 5.5.
We're also seeing Argon using 30% fewer tokens on average than Claude models. It's a really efficient model!