Model comparison
Gemini 4 Argon vs GPT-6.1 Sol: which is cheaper, and which should you use?
Gemini 4 Argon and GPT-6.1 Sol cost about the same: a support chatbot handling 1,000 requests a day comes to about $169.57 a month on Gemini 4 Argon and $169.57 on GPT-6.1 Sol, so the details decide: they differ on cache-write price, long-prompt pricing, context window and reply limit. Gemini 4 Argon lists $2 input and $10 output per million tokens; GPT-6.1 Sol lists $2 and $10. Gemini 4 Argon is priced here at its introductory rate, which runs until 30 November 2026. Context: 1,048,576 vs 1,050,000 tokens. Prices checked 2026-10-16.
Argon is Google’s new flagship and Sol is OpenAI’s everyday model, so they meet on most shortlists for agents and long-document work. Argon launched on an introductory price that rises later, which changes the comparison over time.
- Input / 1M
- $2
- Output / 1M
- $10
- Context
- 1,048,576
- Max output
- 65,536
Google lists this price until 30 November 2026. From 1 December 2026, Gemini 4 Argon costs $4.00 input and $20.00 output per million tokens, with cached input at $0.20.
Full Gemini 4 Argon pricing and specs- Input / 1M
- $2
- Output / 1M
- $10
- Context
- 1,050,000
- Max output
- 128,000
Verdict
Which should you pick, Gemini 4 Argon or GPT-6.1 Sol?
Gemini 4 Argon and GPT-6.1 Sol have about the same list prices per token. On our data, Gemini 4 Argon has the edge for very long prompts and non-text inputs, and GPT-6.1 Sol for long replies. For scale, a support chatbot handling 1,000 requests a day costs about $169.57 a month on Gemini 4 Argon and $169.57 on GPT-6.1 Sol.
- Lowest bill for typical workloadsEither
- Both cost about the same on all 4 workloads below.
- Very long prompts (whole codebases, long documents)Pick Gemini 4 Argon
- Both read about 1,048,576 tokens per request. One 830,000-token prompt with a 2,000-token reply costs $1.68 on Gemini 4 Argon and $3.35 on GPT-6.1 Sol. GPT-6.1 Sol charges $4 / $15 per 1M once a prompt passes 272,000 tokens.
- Long replies (reports, large code files)Pick GPT-6.1 Sol
- GPT-6.1 Sol can write up to 128,000 tokens in one reply, against 65,536 for Gemini 4 Argon.
- Images, audio, video or files in the promptPick Gemini 4 Argon
- Gemini 4 Argon also accepts audio and video, which GPT-6.1 Sol doesn’t.
- Repeated long prompts (prompt caching)Either
- Both bill cached input at about $0.10 per 1M tokens.
- Overnight batch jobsEither
- Both offer batch prices and cost about the same on the document summariser workload.
- Self-hosting or choosing your own hostEither
- Neither has downloadable weights: both are only available through their provider’s API and cloud partners.
Criteria use only list prices, published limits and the features each provider declares. We don’t rank answer quality; test both models on your own prompts before you commit.
Specs
How do Gemini 4 Argon and GPT-6.1 Sol compare on specs?
| Spec | Gemini 4 Argon | GPT-6.1 Sol |
|---|---|---|
| Provider | OpenAI | |
| Input / 1M tokens | $2 | $2 |
| Output / 1M tokens | $10 | $10 |
| Cached input / 1M | $0.10 | $0.10 |
| Cache write / 1M | No write charge listed | $2.50 |
| Batch in / out | $1 / $5 | $1 / $5 |
| Long-prompt price | None | $4 / $15 over 272,000 |
| Context window | 1,048,576 | 1,050,000 |
| Max output | 65,536 | 128,000 (better) |
| Accepts | text, images, files, audio, video | text, images, files |
| Image input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning mode | Yes | Yes |
| Prompt caching | Yes | Yes |
| Structured output | Yes | Yes |
| Open weights | No | No |
| Knowledge cutoff | Not published | Not published |
| First listed | 2026-10-13 | 2026-09-29 |
Prices in US dollars per million tokens. Highlighted: the lower price or larger limit where the difference is over 5%. Features are as declared by each provider’s API; “First listed” is when our data source first listed the model. Long-prompt prices apply to the whole request once the prompt passes the threshold.
Costs
What do Gemini 4 Argon and GPT-6.1 Sol cost for real workloads?
| Workload | Tokens in / out | Requests/day | Gemini 4 Argon / month | GPT-6.1 Sol / month | Cheaper |
|---|---|---|---|---|---|
| Support chatbotCalculator: Gemini 4 Argon · GPT-6.1 Sol | 1,500 / 400 | 1,000 | $169.5750% cached | $169.5750% cached | About the same |
| RAG appCalculator: Gemini 4 Argon · GPT-6.1 Sol | 6,000 / 500 | 500 | $223.8720% cached | $223.8720% cached | About the same |
| Coding agentCalculator: Gemini 4 Argon · GPT-6.1 Sol | 40,000 / 2,000 | 200 | $238.4780% cached | $238.4780% cached | About the same |
| Document summariserCalculator: Gemini 4 Argon · GPT-6.1 Sol | 8,000 / 600 | 300 | $100.38batch | $100.38batch | About the same |
Each row uses the same token counts for both models and list prices, with caching and batch discounts only where the provider publishes them. A month is 365 ÷ 12 days. The support chatbot reads 50% of its prompt from the cache. The RAG app reads 20% of its prompt from the cache. The coding agent reads 80% of its prompt from the cache. The document summariser runs as a batch job where a batch price exists. Open either model in the LLM cost calculator to change any number.
Tokenizers
Are their per-token prices comparable?
Not exactly. Each model splits text into tokens its own way, so the same prompt can be a different number of tokens on Gemini 4 Argon and GPT-6.1 Sol, and the cheaper per-token price isn’t always the cheaper bill. Where a tokenizer isn’t public or measured we say so rather than guess.
| Model | Tokenizer | Tokens per 1,000 words | Output per 1M words |
|---|---|---|---|
| Gemini 4 Argon | We haven’t measured Gemini 4 Argon’s tokenizer yet (Google’s countTokens API gives exact counts). | ||
| GPT-6.1 Sol | OpenAI hasn’t published the tokenizer GPT-6.1 Sol uses, so its count for a given text isn’t known exactly. | ||
English prose, measured on the Universal Declaration of Human Rights (2026-10-11) or taken from the provider’s published words-per-token figure. Code, JSON and other languages use more tokens per word. Count your own text in the token counter or convert with tokens to words.
FAQ
Gemini 4 Argon vs GPT-6.1 Sol questions
Is Gemini 4 Argon cheaper than GPT-6.1 Sol?
Gemini 4 Argon costs $2 per million input tokens and $10 per million output tokens; GPT-6.1 Sol costs $2 and $10. For a support chatbot handling 1,000 requests a day, that is about $169.57 a month on Gemini 4 Argon against $169.57 on GPT-6.1 Sol, so neither is meaningfully cheaper there. Try your own numbers in the LLM cost calculator.
Which has the bigger context window, Gemini 4 Argon or GPT-6.1 Sol?
Their context windows are about the same size. Gemini 4 Argon reads up to 1,048,576 tokens (roughly 786,432 English words) and writes up to 65,536 tokens per reply. GPT-6.1 Sol reads up to 1,050,000 tokens (roughly 787,500 English words) and writes up to 128,000 tokens per reply. The window is shared between your prompt and the reply. Word counts use a rough 0.75 words per token; real ratios depend on the tokenizer.
Is Gemini 4 Argon better than GPT-6.1 Sol?
We don’t score answer quality, so no page of ours can honestly say one is better overall. On what we can measure, Gemini 4 Argon has the edge for very long prompts and non-text inputs, and GPT-6.1 Sol has the edge for long replies. Run both on a sample of your own prompts and compare the answers and the bill before you choose.
Is Gemini 4 Argon or GPT-6.1 Sol better for coding?
We don’t publish benchmark scores, so this page can’t say which writes better code. What we can show is cost: a coding agent re-sending 40,000 tokens of context (80% cached) and writing 2,000 tokens, 200 times a day, costs about $238.47 a month on Gemini 4 Argon and $238.47 on GPT-6.1 Sol. Both support tool calling. Test both on tasks from your own repository.
Can I switch from Gemini 4 Argon to GPT-6.1 Sol without rewriting my code?
Through OpenRouter, yes: both use the same OpenAI-compatible API, so you only change the model ID (google/gemini-4-argon to openai/gpt-6.1-sol). Calling Google and OpenAI directly, the request formats differ; the chat format converter translates between them. Re-test your prompts either way.
Are Gemini 4 Argon and GPT-6.1 Sol open source?
No. Neither Gemini 4 Argon nor GPT-6.1 Sol has published weights: you can only use them through Google’s and OpenAI’s APIs and their cloud partners. If you need a model you can host yourself, compare open-weight options in the model comparison table.
Do Gemini 4 Argon and GPT-6.1 Sol count tokens the same way?
Not necessarily. Each model splits text into tokens with its own tokenizer, so the same prompt can be a different number of tokens on each, and per-token prices aren’t directly comparable. We haven’t measured Gemini 4 Argon’s tokenizer yet (Google’s countTokens API gives exact counts). OpenAI hasn’t published the tokenizer GPT-6.1 Sol uses, so its count for a given text isn’t known exactly. Count your own text with the token counter or convert with tokens to words.