Sol is the economical baseline. Astra needs a task-level reason.
At Standard uncached rates, equal input and output usage costs five times as much on Astra. The independent Max-effort composite is close in this snapshot. That makes Sol worth testing first, while leaving room for Astra on work where missed findings or rework are expensive.
A close composite can hide different strengths.
| Metric | GPT‑6.1 Sol | GPT‑6 Astra |
|---|---|---|
| Intelligence Index ↑ | 52 | 53 |
| Terminal-Bench 4.0 ↑ | 56% | 59% |
| AutomationBench-AA ↑ | 65% | 68% |
| GDPval-AA v2.1 ↑ | 1594 | 1573 |
| Weighted Index cost / task ↓ | $0.72 | $3.26 |
| Weighted output tokens / task | 38k | 27k |
Published independent measurements, not a VSModels test. Rounded results and a one-point Index difference do not establish statistical equivalence. Max labels do not fix equal compute or equal runtime.
Astra uses fewer weighted output tokens here but still has the larger task bill. Sol has the higher GDPval result in this snapshot, so an overall ordering should not substitute for the evaluation closest to your work.
One maintenance case makes the tradeoff concrete.
In an October 14 first-party case study, an OpenAI engineer reviewed stale-experiment findings from a repository audit. The reported results were:
| Reported configuration | Reviewed findings | API cost | Calculated cost / finding |
|---|---|---|---|
| GPT‑6 Astra Ultra | 142 | $109.06 | $0.768 |
| GPT‑6.1 Sol Ultra | 131 | $15.12 | $0.115 |
| GPT‑6.1 Sol Medium | 86 | $5.27 | $0.061 |
The source uses “Ultra” as its configuration label; it is not the API’s Ultrafast pricing tier. Costs include follow-up work and research subagents. The author describes dependencies that Astra caught and Sol missed. Treat this as evidence of a particular workflow, not a general 92% capability claim.
For your own audit, count validated findings that lead to a useful change. A cheaper run that misses an important dependency can be worse than a more expensive one; a long list of low-value suggestions can also waste review time.
Find the point where quality pays for itself.
| Token category | Sol 6.1 | Astra |
|---|---|---|
| Uncached input | $2 | $10 |
| Cached reads | $0.10 | $1 |
| Cache writes | $2.50 | $12.50 |
| Billable output | $10 | $50 |
The fivefold ratio applies to equal uncached usage. Cached reads have a different ratio, and both models apply a long-input premium above 272,000 input tokens. Batch, faster processing and tools are separate considerations.
With the calculator’s default workload, Sol costs $0.04 per attempt and Astra $0.20. At 20% versus 100% acceptance, their calculated API cost per accepted result is equal. That example ignores the cost of your time; it is a break-even exercise, not an observed pass rate.
Set the quality threshold for your workload.
Standard uncached text rates, up to 272,000 input tokens per attempt. No cache, long-context premium, tools, images, faster processing, tax or gateway markup included. Attempts are assumed billed; acceptance does not imply free retries. No provider request is made.
Use both models on the same representative task set. If Astra mainly helps a small subset, evaluate escalation for that subset. Keep privacy, tools and review rules the same so the result measures a model choice rather than two different workflows.
Common questions
Is Sol 6.1 simply a cheaper Astra?
They are separate models. Similar aggregate results do not prove identical behavior, architecture or reliability. Use the exact model IDs and evaluate your own tasks.
Do they have the same context limit?
Both official model pages list 1,050,000 context tokens and a 128,000-token maximum output. A large context limit is not a guarantee that every detail will be used correctly.
Should I send every task to Astra?
A useful evaluation is to start routine work on the cheaper model and measure escalation on failures. Use Astra when its extra accepted quality or lower review burden pays for the difference. This is a workflow suggestion, not a VSModels routing feature.
Sources, method and access
Prices and specifications are a dated documentation snapshot. Calculators run in your browser and estimate supplier API costs; they do not call a model or quote VSModels credits. Vendor claims and independent evaluations are labeled separately. VSModels has not run a paid head-to-head test for this guide and does not offer live calls to the models covered here.
- OpenAI · GPT‑6.1 Sol model and Standard prices
- OpenAI · GPT‑6 Astra model and Standard prices
- Artificial Analysis · Sol Max vs Astra Max
- OpenAI · maintenance case study, October 14, 2026
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