GPT-6 Astra lists at 2.5 times Sol's price. On coding tasks it costs 15% more.
Astra scores 53 to Sol's 47 and lists at $10 / $50 against $4 / $20. Artificial Analysis measured the real gap per coding task at about 15%. Why.
GTM Architect & Growth Operator · Now · 16 September 2026
TL;DR · Key insights
- GPT-6 Astra lists at $10 / $50 per million tokens and GPT-5.6 Sol at $4 / $20. That is 2.5 times the price for six more points on Artificial Analysis's Intelligence Index v4.3, 53 against 47.
- Per task, the gap shrinks. Artificial Analysis measured Astra at $7.09 per coding task, about 15% more than Sol, for a Coding Agent Index score seven points higher. Astra uses far fewer tokens to finish.
- Artificial Analysis also reports Astra cutting the hallucination rate from Sol's 92% to 51% at max effort. For work where a confident wrong answer is expensive, that line matters more than the index.
- Sol's current price is promotional through at least 21 November. If it moves to the $5 / $30 its discount implies, the list-price gap narrows to 2x on input and 1.67x on output.
GPT-6 Astra shipped at $10 / $50. Sol, the model it succeeds at the top of OpenAI’s lineup, lists at $4 / $20. On the price page that is 2.5 times the money.
Artificial Analysis measured something else: what each model actually costs to finish a coding task. That number tells a very different story.
| Info | GPT-6 Astra | GPT-5.6 Sol |
|---|---|---|
| Input / output per 1M | $10 / $50 | $4 / $20 |
| Price status | Standard | Promotional, to at least 21 Nov |
| Cost per coding task | $7.09, ~15% above Sol | Not published |
| Intelligence Index v4.3 | 53 | 47 |
| Coding Agent Index | 62 (in Codex) | 55 |
| Hallucination rate, max effort | 51% | 92% |
| Output speed, tokens/s | 52.9 | 64.7 |
| Cost to run the full index | $5,324 | $3,465 |
| Knowledge cutoff | 30 Apr 2026 | 16 Feb 2026 |
| Lowest reasoning effort | low | none |
Prices, cutoffs and effort levels from OpenAI's model pages for each. Index, speed and run cost from Artificial Analysis model pages on Intelligence Index v4.3; cost per coding task, Coding Agent Index and hallucination rates from Artificial Analysis's GPT-6 Astra benchmarking note. Read on 16 September 2026.
List price says 2.5x. Cost per coding task says about 1.15x. The rest of this piece is about why those two numbers are so far apart, and what it means for the decision.
Price per token is not price per job
Artificial Analysis reports that at max effort Astra costs $7.09 per coding task, about 15% more than GPT-5.6 Sol, for a Coding Agent Index score seven points higher.
The mechanism is token count. Cost per task is the rate multiplied by how many tokens the model spends getting to the end, and Astra spends few. Artificial Analysis measured it at about 27,000 output tokens per task at max effort. A model that costs 2.5 times as much per token and finishes in far fewer of them ends up close in cost per finished job.
The upgrade looks expensive on the price page and close to even on the invoice. That is the same pattern I described for Sonnet 5 in reverse: a low rate with a high step count can cost more than a high rate that finishes fast.
The seven-point coding lead is not uniform either. Artificial Analysis attributes it to Terminal-Bench v4.0, 56% against 37%, and SWE-Atlas-QnA, 62% against 54%, partly offset by DeepSWE, where Sol scores higher at 72% against Astra’s 68%. Terminal work is where the gap is widest. If your coding work looks more like DeepSWE’s long-horizon repository tasks, the gap on your tasks may be smaller or reversed.
The full-index run cost points the same way from a different angle. Artificial Analysis spent $5,324 running its Intelligence Index on Astra and $3,465 on Sol. That is 54% more, not 150% more.
The hallucination line
Artificial Analysis reports that Astra hallucinates half as much as Sol on AA-Omniscience, its knowledge and hallucination benchmark: the rate falls from 92% to 51% at max effort. It adds that this did not come at the cost of accuracy, which rose by four points.
I would read that line before the index for any work where a confident wrong answer is expensive: research summaries that go into a decision, extraction feeding a database, anything a customer reads without a human in between. A six-point index gain is an average across many evaluations. A hallucination rate that almost halves is a specific failure mode becoming much rarer.
Where Astra now sits
When I wrote about Astra’s launch in GPT-6 Astra against Claude, it ranked fourth on the index version current at the time. Artificial Analysis published v4.3 on 7 September, which upgraded Terminal-Bench to 4.0 and added an automation benchmark. On v4.3, Astra scores 53, level with Claude Fable 5.1 at the top.
That is a reason to compare index numbers only within one version. It is also a reason Astra against Sol is now a more interesting question than it was on launch day.
Sol’s price has a date on it
OpenAI’s Sol page describes $4 / $20 as a 20% reduction in input pricing and a 33% reduction in output pricing, promotional at least through 21 November 2026. The discount implies a reference price of $5 / $30. OpenAI does not say that is what Sol costs afterwards.
If Sol does move to $5 / $30, the list-price gap to Astra narrows from 2.5x to 2x on input and 1.67x on output, and the cost-per-task gap narrows with it. Astra’s own price is not described as promotional.
When to upgrade
| The work | Model | Why |
|---|---|---|
| Agentic coding | GPT-6 Astra | Seven Coding Agent Index points for about 15% more per task is an easy trade. |
| Research or extraction where errors are costly | GPT-6 Astra | Hallucination rate reported at 51% against Sol's 92%. |
| Short tasks a user waits on | GPT-5.6 Sol | 64.7 against 52.9 tokens per second, and cheaper per token. |
| Work that must run without reasoning | GPT-5.6 Sol | Astra's lowest effort level is low. Sol supports none. |
| High-volume, low-ambiguity work | Neither | Terra or Luna, which cost a fraction of either for work that does not need a flagship. |
Upgrade the work where cost per task and error rate decide, keep Sol where speed and per-token price decide.
For Astra against Anthropic’s models, see GPT-6 Astra against Claude. For Sol against its Anthropic counterpart, see Opus 5 against Sol.
What would change my mind
A cost-per-task comparison outside coding. The 15% figure is specific to Artificial Analysis’s coding tasks, and on work where Astra’s token efficiency is smaller the gap could widen back toward the list-price ratio.
Sol’s price after 21 November. A permanent $4 / $20 widens the case for staying on Sol; a move to $5 / $30 narrows it.
An independent hallucination measurement on a second benchmark. A drop from 92% to 51% is large enough that I want to see it replicated before I treat it as settled.
Questions people asked
Is GPT-6 Astra better than GPT-5.6 Sol?
Yes, on every published measure I can find: 53 against 47 on the Intelligence Index v4.3, 62 against 55 on the Coding Agent Index, and a reported hallucination rate of 51% against 92%. Sol is faster and cheaper at list price.
How much more does GPT-6 Astra cost than GPT-5.6 Sol?
2.5 times as much at list price, $10 / $50 against $4 / $20. Per coding task, Artificial Analysis measured about 15% more, at $7.09, because Astra uses far fewer tokens.
Should I upgrade from GPT-5.6 Sol to GPT-6 Astra?
For coding and error-sensitive work, yes. For short, latency-sensitive or high-volume work where Sol already succeeds, stay on Sol. Astra also cannot run with reasoning effort set to none.
Why is GPT-6 Astra cheaper per task than its price suggests?
Because cost per task is price multiplied by tokens used, and Astra uses about 27,000 output tokens per task at max effort, which keeps its cost per finished job close to Sol’s.
If you are deciding whether to move a production workload between these two, the contact page is the fastest route to me.
