GPT-6.1 Sol vs Gemini 4 Hydrogen
GPT-6.1 Sol and Gemini 4 Hydrogen are within three points on the Models at Work leaderboard, which we treat as a tie (70 vs 69 out of 100). On independent tests alone they are also level (81 vs 78). Gemini 4 Hydrogen is cheaper: 1,000 support replies cost about $7.50 at list price, against $10 on GPT-6.1 Sol, which is 1.3 times as much. On the Artificial Analysis Intelligence Index, one of the independent tests, GPT-6.1 Sol leads 55 to 51.
| GPT-6.1 Sol · OpenAI | Gemini 4 Hydrogen · Google | |
|---|---|---|
| Leaderboard rank | #6 | #9 |
| Score (0–100) | 70 | 69 |
| Kind of work | Everyday default | Everyday default |
| Price per 1M tokens | $2 to read · $10 to write | $1.50 to read · $7.50 to write |
| Reads at once | 1M tokens (about 750,000 words) | 1M tokens (about 750,000 words) |
| Where you can get it | OpenAI API, Amazon Bedrock, Microsoft Foundry, Gemini Enterprise Agent Platform (Google Cloud), ChatGPT Plus, Pro, Business, Enterprise and Edu, Microsoft 365 Copilot | Gemini Enterprise Agent Platform (Google Cloud), Google AI Studio, Gemini for business, Gemini Enterprise, Gemini app |
| Can a company host it itself | No | No |
| Artificial Analysis Intelligence Index | 55 | 51 |
| Humanity's Sixth Sense (Scale) | 46.60 | Not measured |
| Vals Finance Index | Not measured | 66.14% (rank 2) |
| Vals Tax Agent Bench | Not measured | 52.30% (rank 1) |
| Vals Legal Research Bench | Not measured | 53.85% (rank 6) |
| Best for | Drafting proposals and reports, Summarising long documents, Back-office tasks with several steps, Answering questions from company documents | Everyday drafting and summarising, Spreadsheet models and forecasts in Google Sheets, First-pass tax and finance research, checked by a person, Multi-step tasks across Gmail and Drive |
Cost of 1,000 jobs
| 1,000 of these | GPT-6.1 Sol | Gemini 4 Hydrogen |
|---|---|---|
| Support repliesthe customer message, the account notes and two help articles read; a 300-word reply written | $10 | $7.50 |
| Documents processeda two-page invoice or form read; the fields pulled out | $7 | $5.25 |
| Calls summariseda 40-minute call transcript read; a summary and next steps written | $26 | $20 |
| Contracts revieweda 40-page contract read against a checklist; a memo of issues written | $75 | $56 |
| Drafts writtena brief and one example read; a 600-word email or proposal section written | $11 | $8.25 |
Worked out from each vendor’s list price and a fixed size for each job. A product built on a model charges its own price on top. See what every model costs for the same jobs.
Choose GPT-6.1 Sol for
- Drafting proposals and reports
- Summarising long documents
- Back-office tasks with several steps
- Answering questions from company documents
The sensible OpenAI default: 55 on Artificial Analysis's index against 57 for GPT-6 Astra, at a fifth of Astra's list price.
Caveats: Two points separate it from Astra on the index, which is within noise; test Astra only where Sol's answers fall short. The ChatGPT plans are listed from our researcher's reading of OpenAI's launch page, which blocked automated reading this run; on ChatGPT Enterprise and Edu an owner has to switch the model on. In Microsoft 365 Copilot it is rolling out in phases across Word, Excel, PowerPoint and Chat with usage limits Microsoft has not published, per Microsoft's 30 September post; admins commenting there report users already reaching them.
Choose Gemini 4 Hydrogen for
- Everyday drafting and summarising
- Spreadsheet models and forecasts in Google Sheets
- First-pass tax and finance research, checked by a person
- Multi-step tasks across Gmail and Drive
Scores 51 on Artificial Analysis's index, level with the dearer Gemini 4 Argon (50), at $1.50 in and $7.50 out per million tokens: 25% under Argon and Carbon today and 62.5% under them from 1 December.
Caveats: Released 12 November 2026: one independent test counts toward its score so far. Vals AI's tax, legal and finance tests are recorded below but not yet scored, because fewer than three models on this board carry them. Google sells it as the successor to Gemini 3.8 Flash, but it costs twice what 3.8 Flash does until 1 January 2027, when Google's pricing page says 3.8 Flash rises to the same $1.50 in / $7.50 out per million tokens. On Vals AI's tax test it ranks first with 52.3% of questions right, so close to half its answers there were wrong: a person still checks the output. In Gemini Enterprise it is switched off until an administrator turns it on, per Google Cloud's release notes. Google does not say which Gemini app plans get it or whether it becomes the default in Gemini for business.
What people running them say
GPT-6.1 Sol: The launch thread on Hacker News, a developer forum, argued over its own title: 'near-Astra for a fifth of the price' drew 955 comments, most of them about which work to send to Sol and which to a dearer model.
Gemini 4 Hydrogen: On the Hacker News (a developer forum) launch thread, 534 upvotes, most comments are about Google's model names. On substance: modeless reads Google's charts as 'a better choice than Sonnet in areas outside of coding'; onlyrealcuzzo calls early results 'disappointing', reporting it does more than asked; ComputerGuru notes it costs more than anyone pays for 3.8 Flash today. Developers on day one, none verified, and too little to score.
Questions people ask
Which is better, GPT-6.1 Sol or Gemini 4 Hydrogen?
GPT-6.1 Sol and Gemini 4 Hydrogen are within three points on the Models at Work leaderboard, which we treat as a tie (70 vs 69 out of 100). On independent tests alone they are also level (81 vs 78). Gemini 4 Hydrogen is cheaper: 1,000 support replies cost about $7.50 at list price, against $10 on GPT-6.1 Sol, which is 1.3 times as much. On the Artificial Analysis Intelligence Index, one of the independent tests, GPT-6.1 Sol leads 55 to 51.
When should I choose GPT-6.1 Sol over Gemini 4 Hydrogen?
Choose GPT-6.1 Sol for drafting proposals and reports, summarising long documents, back-office tasks with several steps, answering questions from company documents. The sensible OpenAI default: 55 on Artificial Analysis's index against 57 for GPT-6 Astra, at a fifth of Astra's list price.
When should I choose Gemini 4 Hydrogen over GPT-6.1 Sol?
Choose Gemini 4 Hydrogen for everyday drafting and summarising, spreadsheet models and forecasts in google sheets, first-pass tax and finance research, checked by a person, multi-step tasks across gmail and drive. Scores 51 on Artificial Analysis's index, level with the dearer Gemini 4 Argon (50), at $1.50 in and $7.50 out per million tokens: 25% under Argon and Carbon today and 62.5% under them from 1 December.
Which is cheaper, GPT-6.1 Sol or Gemini 4 Hydrogen?
GPT-6.1 Sol costs $2 per million tokens it reads (input) and $10 per million tokens it writes (output) on OpenAI's list price (OpenAI API pricing, read Nov 13, 2026). A token is about three-quarters of a word. Gemini 4 Hydrogen costs $1.50 per million tokens it reads (input) and $7.50 per million tokens it writes (output) on Google's list price (Google: Introducing Gemini 4 Hydrogen, read Nov 13, 2026). A token is about three-quarters of a word.
What do 1,000 jobs cost on GPT-6.1 Sol and Gemini 4 Hydrogen?
At list price: 1,000 support replies cost $10 on GPT-6.1 Sol and $7.50 on Gemini 4 Hydrogen; 1,000 documents processed cost $7 on GPT-6.1 Sol and $5.25 on Gemini 4 Hydrogen; 1,000 calls summarised cost $26 on GPT-6.1 Sol and $20 on Gemini 4 Hydrogen; 1,000 contracts reviewed cost $75 on GPT-6.1 Sol and $56 on Gemini 4 Hydrogen; 1,000 drafts written cost $11 on GPT-6.1 Sol and $8.25 on Gemini 4 Hydrogen. A product built on either model charges its own price on top.
Scores come from the Models at Work leaderboard: Score is 0 to 100 and computed, not typed. 40% is independent testing (Artificial Analysis, Arena, Scale, Epoch, Vals and others; each test is scaled against the best score on this board, and tests of real work, such as finished freelance projects or professional tasks, count double the exams). 30% is price: the vendor's list price for a typical mix of reading and writing, on a fixed scale from $0.05 to $60 per million tokens, so a model that costs a fifth as much gains real ground. 15% is what people report after running it, from Signals and linked threads. 15% is fit: how much text it can take in at once and where a business can get it (the products and clouds that carry it), with a small credit for open weights. A missing component drops out and the rest are reweighted. A model with no independent test yet is provisional and ranks below every measured one. Within three points is a tie. Vendor-published figures are labelled and never counted. Prices are vendor list prices where published; a typical mix assumes three parts reading to one part writing.