Modelpeers
GPT-6 Astra charactervsGPT-6.1 Sol character

GPT-6 Astra vs GPT-6.1 Sol: Is Astra worth five times the price?

Facts checked Oct 22, 2026. Every number links to its source.

Summary

Derived from sourced facts, not from builder opinions
  • GPT-6.1 Sol costs a fifth of GPT-6 Astra: $2 / $10 per million tokens against $10 / $50.
  • Both scored 58.18% on Terminal-Bench 4.0 in Codex at max effort. Astra's run cost $3,267.18 and Sol's $634.24.
  • Run through the API in the same harness (Mini-SWE-agent) by Vals AI, Astra scored higher: 59.60% against 55.05%.
  • In Codex on a Plus plan, Sol allows about 15-160 local messages per 5 hours and Astra about 5-45. These limits are for Codex and ChatGPT Work, not the API.

Choose GPT-6 Astra if

  • Your own evaluations show a gain on your task that justifies five times the price.
  • You want the higher same-harness Terminal-Bench 4.0 score (59.60% against 55.05%) and the higher Arena WebDev rank.

Choose GPT-6.1 Sol if

  • Cost matters, or you hit Codex limits on a Plus plan.
  • You need Fast mode with EU data residency on the API, which GPT-6 Astra does not offer.
GPT-6 Astra
GPT-6.1 Sol

Follow both to get an email when either one changes its price, limits or behavior.

Best by task

Agentic coding (Terminal-Bench 4.0 official board, both in Codex at max effort)

Tied

Tied at 58.18%. Sol reached it for about 19% of Astra's spend.

Agentic coding (Terminal-Bench 4.0, Vals AI, Mini-SWE-agent harness)

GPT-6 Astra

59.60% against 55.05%, both models run through the API in the same harness.

Web development (Arena WebDev)

GPT-6 Astra

Rank 2 (1775) against rank 4 (1749), with confidence ranges that do not overlap.

Cost per test on Terminal-Bench 4.0 (Vals AI, API prices)

GPT-6.1 Sol

$1.72 per test against $9.58.

Chat preference (Arena text)

Tied

1442 against 1444: within the confidence ranges.

Overall capability (Epoch Capabilities Index)

Tied

168.81 against 168.37: tied within the confidence intervals.

Cost

One request in an agent loop that rereads a repository, so most input is cached. A full task makes many such requests. Illustrative, not measured.

GPT-6 Astra

$0.340 per request

$340.00 a month for 1,000 requests

GPT-6.1 Sol

$0.062 per request

$62.00 a month for 1,000 requests

GPT-6.1 Sol costs 82% less for this workload at list prices.

Estimate per request: (input × input rate + cached input × cached rate + output × output rate) ÷ 1,000,000, at list prices on the cited pricing pages. For GPT-6 Astra, a request with more than 272,000 input tokens is charged 2 times the input rates and 1.5 times the output rate. It is not a measured task cost: models use different numbers of tokens, including reasoning tokens, for the same task.

Side by side

GPT-6 AstraGPT-6.1 Sol
MakerOpenAI
OpenAI
Model IDgpt-6-astra (single snapshot, no dated versions)
gpt-6.1-sol
Released2026-09-03 (API changelog) · ChatGPT rollout began the same day
2026-09-29
API price per 1M tokens$10 input / $50 output · cached input $1 · cache writes $12.50 · prompts over 272K input tokens cost 2x input and 1.5x output · Batch and Flex 50% off · Fast mode 2x
$2 input / $10 output · cached input $0.10 · cache writes $2.50 · prompts over 272K input cost 2x input and 1.5x output · Fast 2x · Ultrafast 6x · Batch and Flex 50% off · regional processing +10%
Context window1,050,000 tokens (max input 922,000)
1,050,000 tokens (max input 922,000)
Max output128,000 tokens
128,000 tokens
Knowledge cutoff2026-04-30
2026-04-30
Reasoning settingslow, medium, high, xhigh, max (no none)
low, medium (default), high, xhigh, max
Where to use itChatGPT Plus, Pro, Business and Enterprise · OpenAI API · Amazon Web Services
OpenAI API (US and EU data residency) · Codex on Plus and Pro
Codex usage on Plus, per 5 hoursAbout 5-45 local messages per 5 hours on Plus and Standard Business
About 15-160 local messages per 5 hours on Plus and Standard Business
Terminal-Bench 4.0 (official board)58.18% (plus or minus 2.79)rank 3, Codex, max effort, 330 trials, $3,267.18 total58.18% (plus or minus 3.11)rank 3 (tie), Codex, max effort, 330 trials, $634.24 total
Terminal-Bench 4.0 (Vals AI, same harness for all)59.60%rank 3, $9.58 per test55.05%rank 7, $1.72 per test
Vals Index v2.265.02%rank 563.94%rank 7
Arena textRank 73 (1442)GPT-6 Astra (Max), 14,076 votesRank 66 (1444)GPT-6.1 Sol (Max), 8,305 votes
Arena WebDevRank 2 (1775)GPT-6 Astra (Max), 6,511 votesRank 4 (1749)GPT-6.1 Sol (Max), 3,414 votes
Epoch Capabilities Index168.81(CI 165.45 to 174.51)168.37(CI 165.0 to 174.43)

Scores appear side by side only when both were published for the same test. Settings differ between sources, so small gaps can reverse under another harness.

Updates

Both GPT-6 Astra and GPT-6.1 Sol

GPT-6 Astra

2 recorded incidents in the last 90 days.

GPT-6.1 Sol

2 recorded incidents in the last 90 days.

FAQ

Is GPT-6.1 Sol as good as GPT-6 Astra?

On the official Terminal-Bench 4.0 board, both scored 58.18% in Codex at max effort. Run through the API in Vals AI's Mini-SWE-agent harness, Astra scored 59.60% and Sol 55.05%.

How much cheaper is GPT-6.1 Sol than GPT-6 Astra?

80% cheaper per token: $2 input and $10 output per million tokens against $10 and $50.

Which gives more Codex usage on a Plus plan?

GPT-6.1 Sol: about 15-160 local messages per 5 hours, against about 5-45 for GPT-6 Astra. ChatGPT Work shares the same allowance.

Do GPT-6 Astra and GPT-6.1 Sol have the same context window?

Yes. Both take 1,050,000 tokens, with at most 922,000 input and 128,000 output.

Which has the newer knowledge cutoff?

Neither. Both have an April 30, 2026 cutoff.

Which is better for coding?

On the official Terminal-Bench 4.0 board in Codex at max effort they tie at 58.18%. Through the API, Vals AI measured Astra at 59.60% and Sol at 55.05%, at $9.58 against $1.72 per test.

Which ranks higher on Arena?

Close on both boards: GPT-6.1 Sol ranks 66th on text and 4th on WebDev, GPT-6 Astra 73rd and 2nd.

Related comparisons

Claude Opus 5.5 vs GPT-6 AstraGPT-6 Astra pageGPT-6.1 Sol page

Sources and method

Prices, specs and limits come from each maker's own pages. Benchmark scores come from independent benchmark publishers and the makers' announcements, with the setting each was measured in. Changes come from changelogs, deprecation pages and status pages. The summary is written from these facts only.