gemini 4 model card

Google made Gemini 4 Carbon broadly available this week, and the model's thin official model card was supplemented by a press announcement that pairs benchmark results with IDE/harness features such as "/swarm." On the MKA multimodal knowledge agent benchmark, which Google built with Artificial Analysis, Gemini 4 Carbon performs roughly on par with Anthropic's models at a top cost of about $4 versus about $32 for Fable, while Google reports that the cheaper Gemini 4 Hydrogen scores above Argon on the Artificial Analysis Intelligence Index. Standard API pricing as of November 15 is $1.50/$7.50 per million input/output tokens for Hydrogen and $0.10/$0.50 for Anthropic's Haiku 5.5 up to 100K tokens ($0.50/$2.50 above 100K).

Gemini 4 Carbon became broadly available this week https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-carbon-now-available/ , and i like to skim the model cards and announcements to see what they can reveal. i actually like the “elements” theme in Gemini’s model names. hydrogen is the light version makes sense , carbon is in the big boys club, and argon? well, like the noble gas, it doesn’t like to mingle: Google first released it to Fairwind for cyber work, including an “argon cyber permissive” version. carbon came afterward and represents an improvement. right now, argon seems positioned as the middle tier between hydrogen and carbon, at least in terms of its intended role. 1 fn:tiers the flag Gemini models keep waving seems to be token efficiency / budget. this seems especially true for the larger models see the comparison with Fable below , though hydrogen’s token prices are higher than Haiku’s.<sup 2 fn:pricing </sup getting a clear picture of the release takes some work, though. Google likes to mix IDE/harness features like “/swarm” with model features. the actual model card https://storage.googleapis.com/deepmind-media/Model-Cards/Gemini-4-Carbon-Model-Card.pdf is very, very thin, while the press announcement is pretty, ah, a mixed bag, i suppose you could call it. on benchmarks, they partnered with Artificial Analysis to create MKA, the multimodal knowledge agent benchmark https://artificialanalysis.ai/evaluations/mka . this seems like a place where that efficiency shows: performance basically on par with Anthropic’s models, at much lower cost. in the chart, the highest Gemini cost is about $4, compared with about $32 for Fable. the evidence around scientific reasoning seems less strong. we get a sort of “testimonial” from Axiom Bio https://www.axi.om/ , but i didn’t find much else. on prompt injection, they seem to be leading the charts. to be honest, this is the first time i’ve seen this specific benchmark, so i don’t have much context for it. at least on this one, they lead the pack. and it’s always nice to see big companies send small winks. the pelican quest video https://www.youtube.com/watch?v=dNbkThtNzS8 is a funny little example. overall, it seems like the teams there have been doing solid work lately. i might get a chance to test these models properly on our own tasks. the gaps between frontier models feel pretty narrow these days, but maybe this particular flavor will turn out to be interesting. not sure yet. this isn’t a clean performance ranking. Google reports https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-hydrogen/ that hydrogen scores above argon on the Artificial Analysis Intelligence Index, while positioning hydrogen for fast execution and argon and carbon for deeper reasoning. ↩ fnref:tiers as of November 15, standard API prices per million input/output tokens are $1.50/$7.50 for hydrogen https://aistudio.google.com/docs/pricing and $0.10/$0.50 for Haiku 5.5 https://www.anthropic.com/claude/haiku for prompts up to 100K tokens $0.50/$2.50 above 100K . token prices alone don’t tell us the cost of completing a task. ↩ fnref:pricing