Gemini 4 Argon vs GPT-6.1 Sol

Quick Answer

These two are the closest match in the frontier tier right now. They launched within a day of each other, list at the same $2 / $10 per million tokens, and sit one point apart on Artificial Analysis’s independent Intelligence Index (Argon 53, Sol 52). The difference that shows up on a bill is token use: GPT-6.1 Sol completed the same benchmark with far fewer output tokens and cost about a third as much per task. Argon’s advantages are Google’s ecosystem, faster generation, a much larger output limit, and broader consumer access in the Gemini app.

For high-volume agent and coding work, GPT-6.1 Sol is the better value on current evidence. For Google-centric work or very long outputs, Argon makes more sense.

At a Glance

Artificial Analysis figures are independent measurements at a point in time. They can change as models and providers update.

What Each Model Is For

Gemini 4 Argon is Google’s top model, positioned for long, multi-step work in software engineering, legal and finance work, and cybersecurity defense. It runs across the Gemini app, AI Mode in Search, Google AI Studio, the paid Gemini API, and Antigravity.

GPT-6.1 Sol is OpenAI’s model for repeated, long-running work. OpenAI says it approaches GPT-6 Astra on agentic coding, computer use, and professional work at about a fifth of Astra’s price, and the independent index supports that: it scores one point below Astra. It powers ChatGPT Work and Codex.

The Token Economics

Identical list prices hide a large practical difference. Argon spent about 110M output tokens to complete Artificial Analysis’s index; Sol spent about 67M. Both charge $10 per million output tokens, so Argon’s longer reasoning shows up directly in cost: about $1.99 per task versus $0.72.

Three things could change that picture for you. Argon’s effort settings can reduce its token use on easier tasks. Argon’s scheduled December price increase would widen the gap further. And Sol reportedly costs more on prompts above about 272K tokens, which matters if you routinely send very large contexts. The number to track is cost per completed task, including retries and the human time spent fixing failures.

Speed and Long Outputs

Argon generated faster in Artificial Analysis’s measurements (about 79 versus 57 tokens per second), though it also generates more. Google says Argon supports up to 1M output tokens, which helps for very long reports or large code changes in one pass.

Benchmarks Beyond the Index

Google’s launch tables show Argon leading or tied on more benchmarks than its rivals, while independent coverage notes it trails on some agentic coding suites. OpenAI’s claims for Sol focus on agentic coding, computer use, and professional work relative to Astra. Both sets are vendor-run. With a one-point gap on the independent index, a small evaluation on your own tasks will tell you more than either company’s charts.

Ecosystem

Argon fits if you work in Google Workspace, Search, Antigravity, or Google Cloud, and it is the model behind the Gemini app’s new Tasks mode on paid plans. Sol fits if you use ChatGPT Work, Codex, or OpenAI’s Agents API. Admin controls, data agreements, and where your team already works usually decide this before the model does.

Choose Gemini 4 Argon If

You work in Google’s ecosystem, need very long outputs, want the model in a consumer app on a $19.99 plan, or your tests show it finishes your tasks with fewer retries.

Choose GPT-6.1 Sol If

You run many agent or coding tasks and cost per task matters, you use Codex or ChatGPT Work, or you want to avoid Argon’s scheduled price increase.

When Neither Is Ideal

For the highest independent score, see Claude Opus 5.5 vs Gemini 4 Argon. For cheap high-volume execution, a worker model such as DeepSeek V4.1 Flash or Gemini 3.8 Flash costs far less; see model routing.

Final Recommendation

On capability, call it a draw. On cost per task, GPT-6.1 Sol is clearly ahead at today’s prices. Pick by ecosystem first, then confirm with a short evaluation on your real workload.

Related Comparisons

• GPT-6 Astra vs Gemini 4 Argon
• GPT-6.1 Sol vs Claude Opus 5.5
• Claude Opus 5.5 vs Gemini 4 Argon
• ChatGPT vs Gemini