GPT-5.6 Sol API pricing

By the aitokensai editors · Verified 2026-11-01 Sources: OpenAI official pricing

OpenAI's heaviest 5.6 tier, deepest reasoning, widest tool use. Available at about 27% below official list.

USD, standard tier. List price cross-checked against OpenAI’s published pricing on 2026-11-01; the discounted route was read from the provider’s live rate config the same day.

Specifications

What GPT-5.6 Sol costs at your volume

Calculated at $2.5 input / $15 output per 1M tokens, 6.0× apart on this model. The 5:1 input-to-output assumption in this table is generous, responses longer than that cost more per response than the row suggests, so treat these as floors rather than estimates. Put your own split through the cost calculator before committing a budget.

Where the money goes on GPT-5.6 Sol

Every conversation with GPT-5.6 Sol is priced twice: what you send costs $2.5 per million tokens, and what comes back costs $15 — 6.0× more. That gap is wide enough to invert the usual advice. Cutting a prompt in half barely moves the bill; halving how much the model writes does. If you are paying $2.5 per million input tokens here, it is because you need the model to think out loud at length, and $15 is what that costs.

Worth saying plainly: for anything bulk and mechanical this rate is hard to justify. A model at a tenth of the price returns the same classification, the same extraction, the same reformatting. The premium buys reasoning on problems where being wrong is expensive, not throughput.

Where GPT-5.6 Sol sits in the index

GPT-5.6 Sol is 203 of 226 on input rate and 213 of 226 on output rate. A gap of 10 places, because on this model the output rate is 6.0× the input rate, steeper than the index median of 4.0× An output-heavy workload therefore leaves it almost where it started, which is why the cheapest model per input token is routinely not the cheapest per task. Percentile is the share of the 226 models in this index that cost more than GPT-5.6 Sol.

On an agent mix the lowest blended rate in the same index is Gemma2 9B It at $0.01 per 1M tokens, about 1187.5× less than this model at the same ratio. Across the whole index, sorting by input price alone moves a model by as much as 74 places; on GPT-5.6 Sol specifically the shift is 10 — which is what the re-ranked index exists to show.

GPT-5.6 Sol is 203 of 226 across every model in the index; the comparison that usually settles a choice is OpenAI's own lineup further down.

GPT-5.6 Sol among OpenAI's 12 models

GPT-5.6 Sol is the 11th cheapest of OpenAI's 12 models in this index at $2.5 per 1M input tokens. The range inside that group runs from GPT-5 nano at $0.025 to GPT-6 Astra at $5 (a spread of 200×, and this one sits at 100).0× the group's cheapest tier.

On input rate alone, stepping up to GPT-6 Astra costs 2.0× the input rate and dropping to GPT-6.1 Sol cuts it by 60%. Both measured at 2026-11-01, the same check as every other rate on this page.

Full OpenAI range, including models outside this shortlist: OpenAI rate index.

Similarly priced alternatives

Blended comparison (input + output per 1M). Price is one axis, these are the three closest to GPT-5.6 Sol in blended rate, not interchangeable substitutes for it.

Calling GPT-5.6 Sol

The identifier you send is gpt-5.6-sol. Copy it exactly, because a mismatch returns a model error rather than a connection error, which sends most people to debug the wrong thing. Everything else is a base URL argument, GPT-5.6 Sol's own SDKs work unchanged.

from openai import OpenAI

client = OpenAI(base_url="https://aicomp.ai/v1", api_key="sk-...")

resp = client.chat.completions.create(
    model="gpt-5.6-sol",
    messages=[
        {"role": "system", "content": "Answer in one short paragraph."},
        {"role": "user", "content": "Explain what changed in this release."},
    ],
    max_tokens=300,
)

# prompt_tokens / completion_tokens 是真实账单的唯一依据 —— 记下来，别猜
print(resp.usage.prompt_tokens, resp.usage.completion_tokens)

Log the usage object on every call, not just while you are optimising. On GPT-5.6 Sol output costs 6.0× what input costs, so the same monthly token count bills very differently depending on how much of it comes back as output — measure your own split before extrapolating from the headline input rate, because rates move with vendor promotions.

Setting it up

Pointing an existing integration at GPT-5.6 Sol is a base URL change, not a rewrite. Pick your tool:

• Claude Code — set the base URL via environment variables
• Cursor — override the API endpoint in settings
• OpenAI / Anthropic SDK — one base_url argument
• Python (sync), streaming and async examples
• Cutting the bill — eight levers ranked by effect

Where GPT-5.6 Sol bills from: the output half

Quoting a monthly token figure tells you very little about GPT-5.6 Sol. Output here costs 6.0× what input does, above the index median of 4.0× across 226 models, so two deployments moving the same number of tokens can differ by several times depending purely on how much the model writes back. Generation is the bill; everything else is rounding. The five shapes below are the ones GPT-5.6 Sol actually gets used for, priced out at each one's real ratio.

The cheapest comparison is GPT-5 nano at $0.025 / $0.2 per 1M — 77.8× cheaper than GPT-5.6 Sol on a blended rate. Treat it as a rate floor, not a recommendation: it says nothing about whether GPT-5 nano can do the work you need GPT-5.6 Sol for.

The spread between the first and last row above is not caused by doing more work — it is caused by asking GPT-5.6 Sol to write more. At 6.0×, the cheapest intervention available to you is shortening responses: a tighter system prompt, a lower max_tokens, a shorter answer format. Optimising the input side barely registers against your $15 per 1M output rate.

FAQ

Get GPT-5.6 Sol access