Google Gemini 4 Argon 缩小了与 OpenAI 和 Anthropic 的差距，但未取得明确领先

Google has unveiled Gemini 4 Argon, its latest flagship model that closes the gap with frontier models from OpenAI and Anthropic, beating some of them on key benchmarks. A new feature: Argon supports up to one million output tokens, letting it work through complex reasoning in a single pass without timing out. Google is rolling out Argon in stages, starting at an introductory price of $2 per million input tokens and $10 per million output tokens, with regular pricing rising to $4 and $20 later. Cached inputs are discounted by 95 percent. Google unveiled Gemini 4 Argon, its new frontier model that closes the gap with rivals from OpenAI and Anthropic, beating some of them on key benchmarks. While it may not clearly lead the pack, it is relatively cheap for a frontier model, at least at the introductory price. Argon is Google's first frontier model in more than seven months, following Gemini 3.1 Pro. It puts the ad giant back among the top three AI labs, though Anthropic likely still holds the lead. After a difficult and drawn-out development period that saw the already-announced Gemini 3.5 frontier model skipped entirely, Google is back in the race. Argon is initially going to a group of "trusted cyber defenders" as part of the Fairwind program . They and Google's internal teams will get the model without cyber guardrails. Google justifies the gradual rollout with a "phased approach" that AI capabilities at this level require. The company is also taking part in the US government's voluntary program that gives agencies access to new models before public release. Ad Feedback from early testers will feed into the model's safety mechanisms. Only after that does Google plan to open Argon up to developers, businesses, and consumers, starting with paying API customers and Google AI Ultra subscribers. The company hasn't given a date, saying only "as soon as possible." Ad Pricing is already set, at least as an introductory rate: $2 per million input tokens and $10 per million output tokens. Cached input tokens cost 95 percent less, working out to about 10 cents per million. Gemini 3.8 Flash had a 90 percent cache discount. That puts Google well below other frontier models on raw token price, though not on token consumption (see below). *Google doesn't state this figure explicitly but says the cache is 95 percent cheaper than the regular input token price. Ad Google also raised the output limit from 64,000 to one million tokens, calling it an industry first. The idea is that if the model can generate hundreds of thousands of tokens in a single trajectory, it can think through hard problems more thoroughly and solve them in one pass. To support this, Google is adding a new "Long Decode Continuation" feature to the Gemini API. It pauses long responses and resumes them through follow-up requests so reasoning doesn't hit a timeout. The input context window stays at one million tokens. Argon accepts text, images, video, and audio as input but only outputs text. Ad Artificial Analysis provides an early independent assessment. At its highest available reasoning level, "High," Gemini 4 Argon scores 53 points on the Artificial Analysis Intelligence Index. That ties it with OpenAI's GPT-6 Astra (max) and Claude Fable 5.1, and puts it one point ahead of GPT-6.1 Sol (max). Ad