Gemini 4 Argon vs GPT-6.1 Sol vs Claude Opus 5.5

Gemini 4 Argon vs GPT-6.1 Sol is a tie on token price until 2026-11-30: both cost $2 per million input tokens and $10 per million output (Gemini API pricing and OpenAI API pricing, read 2026-10-15). On 2026-12-01 Argon moves to $4 and $20, which is what Claude Opus 5.5 already costs (Claude pricing, read 2026-10-15).

All three are flagship models with about a million tokens of context, and all three can search the web from inside the API. This post compares them on what the vendors publish: price per token, the cost of one agent task, context and output limits, built-in search, and the benchmarks each vendor claims. By the end you can pick one on numbers, not on launch posts.

Last checked 2026-10-15, against Google, OpenAI and Anthropic's own pages.

Gemini 4 Argon vs GPT-6.1 Sol vs Claude Opus 5.5 on price

Argon and GPT-6.1 Sol cost the same today, and Opus 5.5 costs twice as much. After 2026-11-30, Argon matches Opus 5.5 and costs twice GPT-6.1 Sol. Cached input is cheapest on Argon and GPT-6.1 Sol; batch halves the price on Argon and Opus 5.5.

GPT-6.1 Sol's prices above are for prompts up to 272K input tokens. Past that, OpenAI lists $4 input and $15 output (OpenAI API pricing, read 2026-10-15). Argon has one price across its whole context window. Every Argon line is broken out in Gemini 4 Argon pricing.

What one agent task costs on each model

Take one task: 20,000 input tokens, 2,000 output tokens including thinking, no caching, no batch. The arithmetic at each vendor's list price:

Task: 20,000 input tokens, 2,000 output tokens

Gemini 4 Argon, through 2026-11-30   20,000 x 2 / 1M + 2,000 x 10 / 1M = 0.060 USD
Gemini 4 Argon, from 2026-12-01      20,000 x 4 / 1M + 2,000 x 20 / 1M = 0.120 USD
GPT-6.1 Sol                          20,000 x 2 / 1M + 2,000 x 10 / 1M = 0.060 USD
Claude Opus 5.5                      20,000 x 4 / 1M + 2,000 x 20 / 1M = 0.120 USD

Token counts are not equal across models. Each vendor uses its own tokenizer and each model thinks for a different length, so the same task can use more tokens on one model than another. Run ten of your real tasks on each and compare the bills.

Context window and output limits

The three context windows are close; the output limits are not. Argon's default output per request is about half of the other two, but it can extend a long answer past that limit.

Built-in web search on each model

Each API has a search tool, and each one bills per search on top of tokens. Google bills each search query Argon decides to run, with 5,000 free a month across Gemini 3 and newer models. OpenAI and Anthropic have no free allowance but a lower price per 1,000.

Anthropic's web fetch tool has no charge beyond tokens, and Google's URL context tool is free as a tool too. The break-even for Google's free allowance, and what an outside search tool costs instead, is in Grounding with Google Search pricing.

Benchmarks: what the vendors' own pages claim

Google's launch post (read 2026-10-15) says Argon ranks first on the Vals Index and scores 87% on the ERQA embodied reasoning test. It names no rival model next to either number. We found no benchmark that all three vendors publish for all three models from the same run, so this post has no score table.

Third-party leaderboards publish their own rankings; read how each one tests before you trust it. If quality decides your pick, run your own tasks on all three and grade the answers. A comparison on the vendors' own pages can only settle price, limits and tools.

Which one fits your agent?

• Lowest token price after November: GPT-6.1 Sol, at half Argon's price from 2026-12-01.
• Lowest price this month: Argon and GPT-6.1 Sol tie; Argon adds 5,000 free searches a month.
• Longest single answer: Argon, through long decode.
• Already on one vendor's cloud: stay there. Argon runs on Google Cloud's Agent Platform at the same global price, and Opus 5.5 runs on Google Cloud, AWS and Microsoft Foundry too.

None of the three can see company records, ranked Google positions or work emails on its own. That is what an MCP data server adds, and it works the same with all three. Gemini 4 Argon MCP shows the Argon setup, and the Gemini 4 Argon API guide covers the key and the first call. If Muse Wonder is on your list too, read Muse Wonder vs Claude Opus 5.5 vs Gemini 4 Argon.

What it cannot do

• looot does not sell tokens for any of these three models. None of them is in looot's catalog today; you pay Google, OpenAI or Anthropic.
• This post does not rank model quality. It compares what the vendors publish.
• Prices change. Google raises Argon's price on 2026-12-01 and edited its pricing page on the day we read it.
• It does not run on a timer. A price watch needs scheduled runs, not available yet.