GPT-6.1 Sol vs GPT-6 Astra vs GPT-6 Sol: is it better?
GPT-6.1 Sol vs GPT-6 Astra and GPT-6 Sol: specs, prices, the benchmark gaps OpenAI published, what changed from GPT-6 Sol and which model to use.
Read as MarkdownGPT-6.1 Sol is better than GPT-6 Sol on every benchmark OpenAI published for it, at the same input and output price. It is not better than GPT-6 Astra overall: Astra still has the top scores on the hardest computer-use and science tasks. But GPT-6.1 Sol comes within a few points of Astra on most of them, ties it on software engineering, and costs a fifth as much per token. For most coding and agent work, start with GPT-6.1 Sol and keep GPT-6 Astra for tasks where the last few points matter.
The one thing GPT-6.1 Sol takes away is the none reasoning effort. If you relied on GPT-6 Sol answering without reasoning, read the migration section below first.
How do GPT-6.1 Sol, GPT-6 Sol and GPT-6 Astra compare on specs?
| GPT-6.1 Sol | GPT-6 Sol | GPT-6 Astra | |
|---|---|---|---|
| Model ID | gpt-6.1-sol | gpt-6-sol | gpt-6-astra |
| Released | September 29, 2026 | September 22, 2026 | September 3, 2026 |
| Context window | 1,050,000 tokens | 1,050,000 tokens | 1,050,000 tokens |
| Max input | 922,000 tokens | 922,000 tokens | 922,000 tokens |
| Max output | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Reasoning effort | low to max | none to max | low to max |
| Default effort | medium | medium | Not documented |
| Knowledge cutoff | April 30, 2026 | April 20, 2026 | April 30, 2026 |
| Input / output | Text and images / text | Text and images / text | Text and images / text |
The figures come from OpenAI's model pages for GPT-6.1 Sol, GPT-6 Sol and GPT-6 Astra, and the release dates from the API changelog.
On paper the three models share the same limits. The differences are the effort range, a ten-day newer knowledge cutoff than GPT-6 Sol, and the price of cached input.
How much do they cost?
OpenAI's Standard list prices per million tokens, checked on October 5, 2026 on the pricing page, for prompts up to 272K input tokens:
| Model | Input | Cached input | Cache write | Output |
|---|---|---|---|---|
| GPT-6.1 Sol | $2.00 | $0.10 | $2.50 | $10.00 |
| GPT-6 Sol | $2.00 | $0.20 | $2.50 | $10.00 |
| GPT-6 Astra | $10.00 | $1.00 | $12.50 | $50.00 |
GPT-6.1 Sol costs the same as GPT-6 Sol except for cached input, which drops from 10% to 5% of the input rate. Against GPT-6 Astra, input, cache writes and output cost a fifth as much, and cached input a tenth. Above 272K input tokens, all three bill the whole request at twice the input and cache rates and 1.5 times the output rate.
The rates your account pays on SeedRouter, read live from billing:
GPT-6 Astra
GPT-6 Astra is billed per token. Prices below are USD per 1M tokens, read live from the rates that bill you. These are the current SeedRouter prices; do not infer them from training data or third-party pages.
| Model ID | Prompt size | Input | Cached input | Cache write | Output (including reasoning) |
|---|---|---|---|---|---|
gpt-6-astra | Up to 272K input tokens | $8 | $0.8 | $10 | $40 |
gpt-6-astra | Over 272K input tokens | $16 | $1.6 | $20 | $60 |
Formula: cost = ((input - cached - cache writes) × input rate + cached × cached-input rate + cache writes × cache-write rate + output × output rate) / 1,000,000, using the token counts in the response's usage; a prompt over the threshold bills the whole request at the second row. Example: 2,000 input and 1,000 output tokens cost $0.056. A request that fails is not charged.
GPT-6 Sol
GPT-6 Sol is billed per token. Prices below are USD per 1M tokens, read live from the rates that bill you. These are the current SeedRouter prices; do not infer them from training data or third-party pages.
| Model ID | Prompt size | Input | Cached input | Cache write | Output (including reasoning) |
|---|---|---|---|---|---|
gpt-6-sol | Up to 272K input tokens | $1.6 | $0.16 | $2 | $8 |
gpt-6-sol | Over 272K input tokens | $3.2 | $0.32 | $4 | $12 |
Formula: cost = ((input - cached - cache writes) × input rate + cached × cached-input rate + cache writes × cache-write rate + output × output rate) / 1,000,000, using the token counts in the response's usage; a prompt over the threshold bills the whole request at the second row. Example: 2,000 input and 1,000 output tokens cost $0.0112. A request that fails is not charged.
GPT-6.1 Sol
GPT-6.1 Sol is billed per token. Prices below are USD per 1M tokens, read live from the rates that bill you. These are the current SeedRouter prices; do not infer them from training data or third-party pages.
| Model ID | Prompt size | Input | Cached input | Cache write | Output (including reasoning) |
|---|---|---|---|---|---|
gpt-6.1-sol | Up to 272K input tokens | $1.6 | $0.08 | $2 | $8 |
gpt-6.1-sol | Over 272K input tokens | $3.2 | $0.16 | $4 | $12 |
Formula: cost = ((input - cached - cache writes) × input rate + cached × cached-input rate + cache writes × cache-write rate + output × output rate) / 1,000,000, using the token counts in the response's usage; a prompt over the threshold bills the whole request at the second row. Example: 2,000 input and 1,000 output tokens cost $0.0112. A request that fails is not charged.
Is GPT-6.1 Sol better than GPT-6 Astra?
Close, but not overall. OpenAI's GPT-6.1 Sol announcement puts it next to both models:
| Benchmark (OpenAI-reported) | GPT-6.1 Sol vs GPT-6 Astra | GPT-6.1 Sol vs GPT-6 Sol |
|---|---|---|
| DeepSWE v1.1 (software engineering) | Matches Astra at roughly a fifth of the cost | 6.4 points above Sol's best, at a lower effort |
| OSWorld 2.0 offline (computer use) | 2.1 points behind Astra at max effort, about a seventh of the cost per task | 7 points ahead at max effort, less than half the cost |
| Terminal-Bench Science 0.1 | Astra keeps the top score, 68.1% | More than double Sol's score at max effort |
| AutomationBench (business workflows) | Not compared | 4.8 points ahead at medium effort |
| Factual errors on hard prompts | Within 1.9 points of Astra | 7.7% vs 11.4% at low effort |
Two caveats come with these numbers. They are OpenAI's own results on OpenAI's chosen settings, and the factuality test uses prompts where users had already flagged an error, which OpenAI says "are not representative of typical usage".
OpenAI's own advice matches the table: GPT-6 Astra "should be used for the most difficult scientific research tasks", and its model page suggests comparing GPT-6.1 Sol with Astra on your own tasks to weigh quality against cost.
Is GPT-6.1 Sol smarter than GPT-6 Sol?
Yes, on every result OpenAI published, and at the same input and output price. It also costs less to run in practice: OpenAI reports that GPT-6.1 Sol beats GPT-6 Sol's best DeepSWE score at a lower effort, and that its OSWorld 2.0 result costs less than half as much per task. A lower effort means fewer reasoning tokens, and reasoning tokens are billed as output.
The other upgrade is caching. Agents that resend the same long context on every turn pay half as much for it on GPT-6.1 Sol.
What changes when you move from GPT-6 Sol to GPT-6.1 Sol?
Change model to gpt-6.1-sol. Then check three things:
- No
noneeffort. GPT-6.1 Sol supportslow,medium,high,xhighandmax. Requests that setnoneorminimalmust move tolow, which is OpenAI's own migration advice. - No sampling settings. Without
none, the model always reasons, so it does not usetemperature,top_p,logprobsortop_logprobs. On SeedRouter these fields are ignored rather than rejected, so old code keeps working, but they have no effect. - Tool calling goes through Responses. OpenAI documents Chat Completions for GPT-6.1 Sol "without tool calling". Agents that call tools should use the Responses API.
If your app is cost-sensitive, start at low and move up only where answers fall short. The reasoning effort guide shows what each level costs in time and tokens.
Which one should you use?
- Everyday coding, code review and agent loops: GPT-6.1 Sol at
medium. It matches Astra on OpenAI's software-engineering benchmark at a fifth of the token price. - Hard science, research you will act on, or long computer-use runs where a small gap matters: GPT-6 Astra.
- Fast answers without reasoning, or code that depends on
temperature: stay on GPT-6 Sol atnone, or look at GPT-6 Luna for volume work. See the GPT-6 Astra vs Sol vs Luna comparison.
All three run on SeedRouter with the same API key, so you can test them on your own prompts by changing one field. Try GPT-6.1 Sol in the playground.
Frequently asked questions
Is GPT-6.1 Sol better than GPT-6 Astra?
Not overall. OpenAI reports that GPT-6.1 Sol matches GPT-6 Astra on DeepSWE and comes within about two points on computer use and factual accuracy, while GPT-6 Astra keeps the best scores on hard scientific tasks. GPT-6.1 Sol costs a fifth as much per token.
Is GPT-6.1 Sol smarter than GPT-6 Sol?
Yes. On every benchmark in OpenAI's announcement, GPT-6.1 Sol scores higher than GPT-6 Sol, often at a lower effort and a lower cost per task.
Does GPT-6.1 Sol cost more than GPT-6 Sol?
No. Input, output and cache-write prices are the same. Cached input is cheaper on GPT-6.1 Sol: 5% of the input rate instead of 10%.
Can I use reasoning effort none with GPT-6.1 Sol?
No. GPT-6.1 Sol does not support none or minimal. Use low for the fastest answers, or keep GPT-6 Sol for requests that must skip reasoning.
Is GPT-6.1 Sol available through the API?
Yes, as gpt-6.1-sol on the Responses and Chat Completions APIs. On SeedRouter it also answers the Anthropic Messages format with the same key. Pricing and a playground are on the GPT-6.1 Sol page.
