GPT-6 Astra vs GPT-5.6 Sol: 51% Hallucination (2026)

Advisor fact-checking is not a chat preference. It is whether a quarterly review memo, an RMD letter, or an IPS update invents a holding, a cost basis, or a tax year. GPT-6 Astra and GPT-5.6 Sol are the two OpenAI flagships an RIA can actually route into that job. Astra is the 3 September 2026 model. Sol is the prior flagship still on the rate card at a lower sticker. This page is only those two products.

On 3 September 2026 Astra is not generally on ChatGPT. Access is limited orgs, Trusted Access, and Foundry Limited Access, with Plus, Pro, Business, Enterprise, API, AWS, and Foundry listed as coming days, and Enterprise stays off until an admin turns it on. Sol remains the model most advisor desks already have. The accuracy question is whether Astra's hallucination drop is worth the list gap, not whether a new chat tile appeared.

TL;DR

• Pick GPT-6 Astra when the job is a supervised advisor memo and you will pay $10 / $50 per 1M tokens to cut AA-Omniscience hallucination at max from 92% (Sol) to 51%, with a 4-point accuracy gain on the same bench.

• Pick GPT-5.6 Sol when the desk already runs Sol, the work is internal scratch, and you want $4 / $20 list plus AA Intelligence cost per task of $0.95 instead of Astra's $1.67.

• Do not put either model on an unsupervised send. Hallucination falling to 51% is still a coin flip on the questions the model gets wrong.

• Orchestrate the review hold in a workflow layer. Native chat, a single Zapier or Make or n8n step, and US Tech Automations are different jobs.

Quick-answer FAQs

Does GPT-6 Astra hallucinate less than GPT-5.6 Sol?

Yes. according to Artificial Analysis, GPT-6 Astra's AA-Omniscience hallucination rate at max effort is 51%, down from 92% on GPT-5.6 Sol, with accuracy up 4 points on the same knowledge bench. That is the independent hallucination number for this pair, not an OpenAI marketing slide.

Can an RIA put Astra on ChatGPT today?

No. On 3 September 2026 Astra is limited-org, Trusted Access, and Foundry Limited Access, with consumer and API seats listed as coming days, and Enterprise off until an admin enables it. Sol is the model already sitting in most paid ChatGPT and API accounts.

What does the $6 input gap actually buy?

List input is $10 per 1M for Astra and $4 per 1M for Sol on OpenAI's standard short-context card, so the gap is $6 per million input tokens before cache and output. What it buys on this page is the hallucination cut and the 4-point accuracy lift, not a cheaper task bill. according to Artificial Analysis, AA Intelligence cost per task at max is $1.67 for Astra and $0.95 for Sol, so Astra is still the more expensive task.

When should Sol stay the default?

Keep Sol when the output is a scratch outline a CFP will rewrite anyway, when the prompt is short, and when you are still on Sol's promotional list of $4 / $20, which OpenAI says remains available at least through 21 November 2026. Move the supervised client-facing draft to Astra once the org can actually call gpt-6-astra.

Should a fact-check workflow skip a human reviewer?

No. A 51% hallucination rate on the questions the model misses is not a send button. The workflow is trigger, draft, hold, CFP check against the CRM household, then archive. Skipping the hold is how an invented RMD year reaches a client.

How do Zapier, Make, or n8n fit this comparison?

They copy a booking or a note from one app to another on the happy path. They are the right buy when Calendly already writes the appointment into Redtail or Wealthbox and nobody needs a model in the middle. They are the wrong buy when the payload is a generated IPS paragraph that must sit in a review queue before it is a client communication.

Who this is for

This page is for RIA operations, CCO staff, and lead advisors who already run a CRM and a calendar, and who want a model to draft review memos, RMD letters, or household summaries without inventing facts. It is not for a chat tourist comparing vibe. It is not for a cyber waitlist. Fit is a supervised writing job with a system of record.

Red flags: no CRM household as the source of truth; no named reviewer on generated client text; using a restricted cyber twin because it sounds "smarter" at facts. Those desks should fix the file and the hold, not the model SKU.

When NOT to use US Tech Automations: stay in native ChatGPT or the API playground if one advisor is pasting notes by hand and the output never leaves the firm. Use Zapier, Make, or n8n if the only required step is copying invitee.created into the CRM and no model drafts client language. Use the CRM's own tasks if Wealthbox or Redtail already owns the reminder and the note. Add the orchestration layer only when the draft must move from calendar to model to reviewer to archive as one run.

The same desk still needs a CRM and a reminder path. Pair the model choice with advisor CRM workflow and quarterly portfolio review reminders so the memo has a household to check against.

How the automation works

The motion is a booked review, a draft, a hold, and an archive. Calendly, or the CRM calendar, creates the meeting. The model writes a first pass from the household file. A CFP or paraplanner checks holdings, AUM, and tax facts against the CRM. Compliance keeps the sent version. None of that is "better chat."

Worked example: when Calendly emits invitee.created for a quarterly review, documented in Calendly's webhook payload, US Tech Automations pulls the household, calls GPT-6 Astra at $10 per 1M input to draft an 8-page IPS update, and parks the draft in a review queue so a CFP can check 12 holdings before send. The same invitee.created path can call GPT-5.6 Sol at $4 per 1M input; that cut is real money, and it is the wrong place to save if the letter is a client communication, because Sol's max hallucination rate on AA-Omniscience was 92%.

The hold is the product. Astra's 51% miss-hallucination rate is a reason to prefer it for the draft step, not a reason to auto-send. Sol's cheaper sticker is a reason to keep it on internal outlines. The workflow should name the model per step, log which SKU wrote the draft, and refuse to send without the reviewer field.

Compliance archiving is a separate pipe. If the sent memo never lands in the archive the CCO already supervises, you built a second set of books. See compliance archiving for advisors for the retention side of the same review.

Benchmarks

Hallucination is the decision. Adjacent benches tell you whether Astra also got generally "smarter" or just less willing to invent. Independent AA Intelligence at max is 61 for Astra and 61 for Sol on the Fable-week board, with OpenAI's own table printing 61.2 versus 60.9. That is a tie on the composite. The omniscience slice is the gap.

Astra max hallucination rate: 51%

Sol max hallucination rate: 92%

Sources: Artificial Analysis Astra article and leaderboard, 2026-09-03; OpenAI GPT-6 Astra launch table, 2026-09-03; OpenAI API pricing, 2026-09-03. OpenAI's table is provider-run. AA is the independent lab.

according to OpenAI, Astra's alignment eval for going beyond the authorized target is 0%, against 48.2% for unsafeguarded GPT-5.6 Sol. That is a safety row, not an omniscience row, and it still matters for an RIA that cannot have a model wander off the household file.

The book size is why a wrong fact is expensive. according to Cerulli Associates (2024), the average advisor book in the RIA channel is $98M AUM. A hallucinated cost basis on a $98M book is not a typo in Slack.

How we evaluated

Weights assume a supervised advisor-writing job, not a desktop-agent bake-off and not a cyber program. A desk that only wants cheaper tokens should raise cost and lower hallucination. A CCO that archives every client letter should raise hold-and-log and keep hallucination first.

Astra wins the hallucination row and loses the cost and access rows on day one. Sol wins cost and access and loses omniscience. Neither row lets you skip the reviewer.

Tool / build comparison

Both models are OpenAI API SKUs. Astra's id is gpt-6-astra. Sol's id is gpt-5.6-sol. Astra has no none reasoning, needs the Responses API for tools, and does not take custom temperature, top_p, or logprobs. Sol remains the cheaper, already-provisioned flagship. Fast mode is 2× Standard on the API docs and 2.5× Standard on the Help Center Codex/Work card; name the surface before you forecast a bill.

List prices from OpenAI API pricing, 2026-09-03. Hallucination and task $ from Artificial Analysis, 2026-09-03. "1" means the desk can use it today without an admin enable; "0" means it cannot.

Do not treat OpenAI's launch table as an independent lab. Use it for access, list price, and the alignment row. Use AA for hallucination and cost per task.

Cost and payback

Sticker and task $ disagree in direction versus "is it worth it for facts." Astra is 2.5× Sol on list input ($10 vs $4) and about 1.75× Sol on AA Intelligence cost per task ($1.67 vs $0.95). The hallucination cut is the thing you are buying. If the output is not a client communication, you are buying the wrong SKU.

according to SIFMA (2024), there are 15,400-plus retail-serving SEC-registered RIAs. Most of those desks will still be on Sol this week. Payback is not "Astra tokens are cheaper." Payback is fewer invented facts in letters a CCO has to unwind.

OpenAI API pricing and Help Center rate card, 2026-09-03. Long-context >272K doubles Astra input/cache and 1.5× output for the full request except Codex, which skips that multiplier and does not bill cache writes. Sol promotional list holds at least through 21 November 2026.

Astra list input: $10 per 1M tokens

A mid-size RIA already spends real money on supervision. according to FINRA (2024), mid-size RIA annual compliance cost runs $750K–$1.5M in the commonly cited $50M–$500M AUM band. Token line items will not move that budget. An invented tax fact in a client letter will.

Pros and cons

GPT-6 Astra

Pros

• Independent AA-Omniscience hallucination at max is 51%, versus 92% on Sol, with a 4-point accuracy gain on the same bench.

• Alignment "beyond authorized target" prints 0% on OpenAI's launch table, against 48.2% unsafeguarded Sol.

• 1.05M context and 128K max output on the Astra card, which is enough to hold a household file plus the draft.

• Same $10 / $50 list family as the other 2026 frontier SKU, so finance can forecast input/output without a surprise third price.

Cons

• Not generally on ChatGPT on 3 September 2026; Enterprise stays off until an admin enables it.

• List input is $10 versus Sol's $4; AA task $ is $1.67 versus $0.95.

• 51% hallucination on missed questions is still a hold, not a send.

• Tools need the Responses API; no custom temperature, top_p, or none reasoning.

GPT-5.6 Sol

Pros

• List $4 / $20 and cached input $0.40, with promotional pricing called out through at least 21 November 2026.

• AA Intelligence cost per task $0.95 at max, the cheaper of this pair.

• Already on paid ChatGPT and API seats, so the desk can run the workflow this afternoon.

• Independent Intelligence Index at max is tied with Astra at 61, so you are not dumping a "dumb" model.

Cons

• AA-Omniscience hallucination at max is 92%, which is the reason this page exists.

• Unsafeguarded alignment "beyond authorized target" on OpenAI's table is 48.2%.

• Using Sol for unsupervised client letters saves tokens and spends CCO time.

• Long-context and Fast-mode multipliers still apply; cheap list is not a cheap runaway loop.

Key Takeaways

• GPT-6 Astra vs GPT-5.6 Sol for advisor facts is a hallucination decision: 51% versus 92% at max on AA-Omniscience, with Astra also +4 accuracy points.

• Astra list is $10 / $50; Sol list is $4 / $20. AA task $ still favors Sol at $0.95 versus $1.67.

• Astra is not generally on ChatGPT on 3 September 2026. Sol is the model you can already call.

• Neither model should send client language without a CRM check and a named reviewer.

• US Tech Automations belongs only when invitee.created (or the CRM equivalent) must draft, hold, and archive as one workflow. Zapier, Make, or n8n is enough when the only job is a copy between two apps.

The category decision is which OpenAI SKU drafts the memo, not which chatbot feels nicer. Put Astra on the supervised client draft when the org can call it. Keep Sol on internal scratch. Route the hold through US Tech Automations only when calendar, model, reviewer, and archive have to be one run; see agentic workflows for that shape.