Google announces Gemini 4 Argon AI model, but you can't use it yet
Google has announced Gemini 4 Argon, a new AI model that claims industry-leading performance in coding, knowledge work, and cybersecurity. Benchmarks show Gemini 4 Argon achieving 77.9 percent on the DeepSWE v1.1 benchmark, surpassing GPT-6 Astra, Fable 5.1, and Opus 5.5. It also scored highest on the Vals Index test for economic analysis. While currently in limited testing, Google has revealed API pricing: $2 per million input tokens and $10 per million output tokens, with a 95 percent discount on cached input tokens. The model will support a 1 million token output limit, a significant increase from previous Gemini models.
Unlike previous Gemini models, Gemini 4 Argon supports a much higher output limit of 1 million tokens, up from 64,000 tokens.
时间与来源
时间显示为 UTC
显示时区：UTC
本地时区尚不可用，暂时显示 UTC。
发布当时偏移：UTC+02026年9月30日 20:11 UTC
收录当时偏移：UTC+02026年9月30日 21:00 UTC
- 发布
- 2026年9月30日 20:11
- 收录
- 2026年9月30日 21:00
- 来源类型
- 媒体报道
- 档位
- 专业媒体
- 信源状态
- 正常
档位是按信源手工设定的编辑判断，不是逐条打分。
讨论趋势
百分比基于采集到的讨论信号，不代表新增评论数或独立参与人数。曲线仅用于同一话题在不同时段的比较。
Google promised Gemini 3.5 Pro in June, but it spent the summer trotting out smaller Flash models. Now, Google is ready to take on the frontier again with Gemini 4 Argon. The company claims this new AI offers industry-leading performance in coding, knowledge work, and cybersecurity, but you aren’t allowed to use it yet.
While most of us will have to wait to test Gemini 4, Google says engineers inside the company are already using the new model extensively. Argon reportedly used “fleet-wide telemetry data” to help Google save 300 TiB of memory across its data centers. Meanwhile, Argon agents have been working to migrate C/C++ codebases to Rust across Google, including thousands of lines in the core re2 and libgav1 libraries and more than 800,000 lines in the Fuchsia OS Zircon kernel.
Google has also come armed with a raft of benchmarks to back up its claims. On the software engineering DeepSWE v1.1 benchmark, Gemini 4 Argon hits 77.9 percent, which is higher than GPT-6 Astra, Fable 5.1, and Opus 5.5. Google promises similar power across a range of long-horizon tasks, pointing to Argon’s industry-leading score in the economic analysis Vals Index test.
This model is still in limited testing, but Google has announced API pricing. For a limited time, Argon will offer rates of $2 per million input tokens and $10 per million output tokens, and cached input tokens will be discounted 95 percent. The company has also confirmed that Gemini 4 Argon will support a much higher output limit of 1 million tokens. That’s up from 64,000 tokens in previous Gemini models. Google says this allows users to complete more daunting tasks in a single step.