GPT-6 Astra alternatives: six models from 2x to 26x cheaper on output
Astra costs $50 per million output tokens. Claude Opus 5 costs $25, Gemini 3.7 Flash $3.75, DeepSeek V4 Pro $1.91 - at near-identical context.
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GPT-6 Astra costs $10 per million input tokens and $50 per million output tokens. That is the most expensive row on our price list, and for a lot of workloads it is money spent on capability nobody is using. Here is what the alternatives actually cost, and where each one stops being a substitute.
The price list
Rates per million tokens, snapshot of 9 September 2026. Every figure below is the published API rate, not a promotional tier.
| Model | Input | Output | Context | Output vs Astra |
|---|---|---|---|---|
| GPT-6 Astra | $10.00 | $50.00 | 1 050 000 | - |
| Claude Opus 5 | $5.00 | $25.00 | 1 000 000 | 2× cheaper |
| Kimi K3 | $3.00 | $15.00 | 1 048 576 | 3.3× cheaper |
| Qwen 3.8 (2.4T) | $2.00 | $6.00 | 1 048 576 | 8.3× cheaper |
| Grok 4.6 | $2.00 | $6.00 | 500 000 | 8.3× cheaper |
| Gemini 3.7 Flash | $0.75 | $3.75 | 1 048 576 | 13× cheaper |
| DeepSeek V4 Pro | $0.96 | $1.91 | 1 048 576 | 26× cheaper |
Note what the context column does not show: a cliff. Five of these six alternatives are within 5% of Astra’s window. Whatever you are paying the premium for, it is not room to put documents in.
What that means on a real bill
A drafting workload - 5 million tokens in, 5 million tokens out per month, which is roughly one full-time writer’s worth of generated text:
| Model | Month | Year |
|---|---|---|
| GPT-6 Astra | $300 | $3 600 |
| Claude Opus 5 | $150 | $1 800 |
| Kimi K3 | $90 | $1 080 |
| Qwen 3.8 | $40 | $480 |
| Gemini 3.7 Flash | $22.50 | $270 |
| DeepSeek V4 Pro | $14.35 | $172 |
Output tokens dominate every one of these totals. That is the practical rule: when you shop for a cheaper model, read the output column first - the input rate is usually a rounding error next to it.
Picking by workload, not by leaderboard
Claude Opus 5 - the like-for-like swap. Same tier of model, half the price, same million-token window. If you adopted Astra by default and never benchmarked it, this is the first thing to try, because it is the change least likely to require rewriting your prompts.
Kimi K3 - long documents on a budget. A million-token window at $15 output puts whole-repository and whole-contract work within reach of a small team. The trade-off is ecosystem maturity: fewer SDK conveniences, fewer people to ask when something behaves oddly.
Qwen 3.8 - when open weights matter. Same price as Grok, twice the context, and the option of moving the workload onto your own hardware later. Worth it if vendor lock-in is a real risk in your plans rather than a slide in a deck.
Gemini 3.7 Flash - high-volume, low-stakes. Thirteen times cheaper on output than Astra. For classification, tagging, extraction and first-draft summaries, the quality difference is usually invisible after a human edit that you were going to do anyway.
DeepSeek V4 Pro - the floor. At $1.91 per million output tokens it is 26 times cheaper than Astra. Check your own data-residency and compliance requirements before you route customer text to it; that, not quality, is what usually rules it out.
Where Astra is still the right answer
Three cases, and they are narrower than the price gap suggests:
- The task fails outright on cheaper models. Not “worse” - fails. Multi-step reasoning that has to hold together across a long chain, where a single wrong link makes the whole output useless.
- Output volume is tiny and review is expensive. If you generate 50 000 tokens a month and a senior person checks every one, the model is not your cost centre. Buy the best and stop optimising.
- You need the extra 50 000 tokens of context over the 1M models - a genuine requirement for a handful of corpus-scale jobs, and nobody else.
How to switch without guessing
Route ten percent of live traffic to the candidate model for a week, keep both outputs, and have whoever normally reviews the work mark which ones they would ship. If the cheaper model’s acceptance rate is within a few points, move the rest. If it is not, you have learned exactly what you are paying the premium for - and that is worth knowing either way.
Prices above are refreshed from vendor price lists; the figures in this article are from the snapshot dated 9 September 2026. Check the current rate before you budget a year on it.
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