# llm-gemini 0.35

> Source: <https://simonwillison.net/2026/Oct/13/llm-gemini/>
> Published: 2026-10-13 22:28:54+00:00

**Release:** [llm-gemini 0.35](https://github.com/simonw/llm-gemini/releases/tag/0.35)

I added support to [llm-gemini](https://github.com/simonw/llm-gemini) for the [new Gemini 4 Argon](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/) model, made available today via the Gemini API and for customers of their $100/month subscription plan.

Here are [the low, medium and high pelicans](https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2Fd741e4420dea14c460f0108ac22dbc26). As expected, they are all excellent: Gemini has a track record of producing great SVGs, and are the only lab where I know their [staff have invested in SVG specifically](https://twitter.com/sunjiao123sun_/status/2024555516551372920) (and who have [boasted about their pelicans](https://simonwillison.net/2026/Feb/19/gemini-31-pro/#jeff-dean) before.)

Here's the "high" illustration, which cost me 17.166 cents:

The pricing is interesting. At launch, Argon is $2/million input and $10/million output - the same price as GPT-6 Sol, half the price of Claude Opus 5.5 and 1/5th the price of Claude Fable 5.1 and GPT-6 Astra.

But on December 1st Argon is set to double in price - so it will be the same price as Opus 5.5.

Prices like this aren't really comparable these days since what really matters is how many tokens a model takes to achieve a goal within an agentic harness.

One useful clue for that comes from Artificial Analysis, who publish [the total cost to run their benchmark](https://artificialanalysis.ai/#total-cost-tabs) using each model. Argon is looking very good there - costing $2,407 to run the benchmark, putting it close to GLM-5.3 and significantly cheaper than OpenAI, Anthropic, and Meta's latest models.

When the price doubles it will still be a little cheaper than GPT-6 Astra.

(I [used ChatGPT to edit that chart](https://chatgpt.com/share/6acebe13-5378-83e8-bf2f-9f4d05b206f4)! The data is all correct, I checked - I needed to get that Gemini 4 Argon info box to display without overlapping the other numbers.)

Some bonus examples using Gemini 4 Argon: here's [Generate an SVG of an armadillo in fishnet tights jaywalking on Mars](https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F9589ff9e0c977bbf3b012b7a11f5bd71), here's [a Fabergé egg](https://tools.simonwillison.net/blender-viewer?url=https%3A%2F%2Fstatic.simonwillison.net%2Fstatic%2Fcors-allow%2F2026%2Fgemini-4-astra-egg.blend) it created for me using Blender, and DeepMind staffer @fofrAI shared [a video of a pelican riding a bike, using fourier epicycles](https://twitter.com/fofrai/status/2110043023954284889). That's a fun new twist!

Tags: [google](https://simonwillison.net/tags/google), [ai](https://simonwillison.net/tags/ai), [generative-ai](https://simonwillison.net/tags/generative-ai), [llms](https://simonwillison.net/tags/llms), [llm](https://simonwillison.net/tags/llm), [gemini](https://simonwillison.net/tags/gemini), [llm-pricing](https://simonwillison.net/tags/llm-pricing), [pelican-riding-a-bicycle](https://simonwillison.net/tags/pelican-riding-a-bicycle), [llm-release](https://simonwillison.net/tags/llm-release)