Gemini 4 Argon lifts output cap to 1 M tokens and doubles pricing
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| Source: Techmeme | Original article
Google's Gemini 4 Argon model now supports up to 1 million output tokens—up from 64 K—and initially costs $2 per M input tokens and $10 per M output tokens, later rising to $4 and $20.
Google DeepMind has revealed that its newest frontier model, Gemini 4 Argon, can now generate up to one million tokens in a single response – a dramatic jump from the 64 K‑token ceiling of earlier Gemini versions. The expansion, announced in the company’s “Introducing Gemini 4 Argon” brief, is positioned as a way to let the model “think deeply” on complex problems, from extensive code generation to long‑form reasoning.
The rollout also includes a two‑tier pricing structure. Early adopters pay $2 per million input tokens and $10 per million output tokens; Google says those rates will double to $4 and $20 respectively after an introductory period. The pricing details were highlighted in a Decoder report by Matthias Bastian and echoed in several industry blogs that tracked the model’s launch.
Why it matters: the token‑output boost removes a key limitation that forced developers to split large tasks into multiple calls, potentially lowering latency and simplifying workflow for applications such as software synthesis, research paper drafting, and detailed data analysis. The introductory pricing makes the capability accessible for experimentation, but the slated increase could shape adoption curves as enterprises weigh cost against the value of ultra‑long outputs.
What to watch next: Google has so far limited Argon to a closed “Fairwind” testing program for trusted cyber‑defenders, with a public API still pending. Observers will be keen to see when broader access opens, how quickly the higher pricing takes effect, and whether the model’s performance on real‑world coding tasks – a point of internal debate noted in earlier coverage – lives up to the benchmark leads it already claims. Further updates on usage patterns and any adjustments to the pricing model will be critical for developers weighing Gemini 4 Argon against competing LLM offerings.
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