GPT-6.1 Sol vs GPT-6 Astra: One Fifth the Price, Within a Point on Most Benchmarks
If you are paying for GPT-6 Astra today, the honest answer after OpenAI's September 29 DevDay is: switch most of your workload to GPT-6.1 Sol, and keep Astra only for long computer-use runs. Sol costs one fifth as much and lands within half a point of Astra on software engineering. That is the whole story, and the rest of this post is the evidence plus the two places the rule breaks.
What the numbers actually say
OpenAI released GPT-6.1 Sol on September 29, 2026, positioned as near-Astra capability at mid-tier pricing. The benchmark spread is unusually tight:
| Benchmark | GPT-6.1 Sol | GPT-6 Astra | Cost per task |
|---|---|---|---|
| DeepSWE v1.1 (coding) | 75.2% | 74.8% | $1.50 vs $7.70 |
| OSWorld 2.0 (computer use) | 71.4% | 73.5% | $1.30 vs $9.30 |
| GDP.pdf (document analysis) | 32.0% | 32.2% | — |
| Terminal-Bench Science 0.1 | — | 68.1% | $5.47 vs $23.80 |
On coding, Sol is not merely close — it is marginally ahead, at roughly a fifth of the per-task cost. On document analysis the two are inside the noise. The only benchmark where Astra holds a visible lead is computer use, and even there the gap is 2.1 points against a 7x cost difference.
Against the competition, GPT-6.1 Sol scores about 36.0% on AutomationBench 1.0.6 versus Claude Opus 5.5's 33.8% at medium effort, at $0.30 per task against $0.92.
The pricing detail that decides your bill
| Model | Input / 1M | Cached input / 1M | Output / 1M | Context |
|---|---|---|---|---|
| GPT-6.1 Sol | $2.00 | $0.10 | $10.00 | 1,050,000 |
| GPT-6 Astra | $10.00 | $1.00 | $50.00 | 1,050,000 |
Two things to plan around before you rewrite your config:
- Cached input is $0.10 per million — a 95% discount. If your application replays a long system prompt or a fixed document on every call, this is where the real saving sits, and it is larger than the headline 5x.
- The million-token window is not priced linearly. Requests above 272,000 input tokens are billed at 2x the input and cache rates and 1.5x the output rate for the entire request. The cheap window is effectively 272K. Crossing it by one token reprices everything before it.
Maximum output is 128,000 tokens, and the API identifier is gpt-6.1-sol.
When Astra is still the right call
Two cases, and they are narrower than most teams assume:
Long agentic computer-use runs. The 2.1-point OSWorld gap sounds ignorable until you chain it. An agent that makes twenty sequential decisions compounds a per-step accuracy difference into a materially different success rate, and a failed twenty-step run costs more than the model price gap ever saved. If your job is "drive a browser for ten minutes unsupervised," pay for Astra.
Work where a mistake is expensive to catch downstream. Not because Astra is broadly more accurate — the benchmarks say it is not — but because on the hardest tail of any distribution, the flagship is the model with the most headroom. Legal review, medical summarization, anything where a human will not re-check the output.
Everything else — code generation, debugging, drafting, extraction, multi-step analysis that finishes in a few turns — is now Sol's job. This is the same logic that applied when GPT-6 Sol and Luna halved the mid and light tiers a week earlier, except the gap Sol has to justify is now much smaller.
How to compare them yourself
Straight from OpenAI, GPT-6.1 Sol is an API and paid-tier model; there is no free ChatGPT path to it.
Being straight with you about what is live on our side: GPT-6 Astra is available now on aiwith.chat as the default of its GPT-6 robot, alongside GPT-6 Sol, GPT-6 Luna, Claude and Gemini. GPT-6.1 Sol is not wired up yet — it launched yesterday, and we add models after testing them rather than on announcement day. If 6.1 Sol specifically is what you came for, check back instead of signing up expecting it today.
What you can do today is the comparison that actually decides your default: run your real task on GPT-6 Astra and on GPT-6 Sol side by side. If GPT-6 Sol already clears your quality bar, GPT-6.1 Sol at the same price with better benchmarks is a strict upgrade whenever it lands, and Astra was never necessary for that workload. If only Astra clears it, you have just identified the jobs worth keeping on a flagship — which is the list you needed before the price war started.
The pattern worth noticing
Astra held the flagship spot for four weeks. In that time OpenAI shipped two rounds of cheaper models that closed nearly the whole quality gap. For anyone paying per token, the move this quarter is not adopting the newest top-end model — it is auditing which of your workloads are still running on one that costs five times what the task requires.
Try GPT-6 free on aiwith.chat — one account covers GPT-6, Claude and Gemini, so the side-by-side does not need three subscriptions.
- GPT-6 Sol vs GPT-6 Luna: Pricing, What Each Is For, and Which One You Actually Need
- GPT-6 Astra Free: How to Try OpenAI's Most Agentic Model Without ChatGPT Plus
- GPT-6 Astra: What OpenAI's Next Model Means (and When You Can Actually Use It)
- GPT-6 Astra vs Gemini 3.1 Pro: Is the 5x Gap Worth It?
- GPT-5.6 Has Three Variants Now. Here's Which One Actually Fits Your Task.
Sources: Vellum, DataCamp, Artificial Analysis.