ModelFare.ai

GPT-5.6 Sol: where to access it & real cost

live on the first-party API by OpenAI text

A million-token context with image input, and a stated point where the rate card changes.

Quick answer prices verified
Best for our call
A million-token context with image input, and a stated point where the rate card changes.
Cheapest
$30.00 at OpenAI API · 1M output tokens · claimed
First-party
$30.00 at OpenAI API · 1M output tokens · claimed
Routes selling
1 of 1 tracked
Verified
2026-08-15

GPT-5.6 Sol, from OpenAI, is purchasable on the one route we track. 1M output tokens costs $30.00 at OpenAI API, the cheapest published rate we can cite.

The figure above buys 1M output tokens. The board below prices 4 units in all, each column named. Figures come from each seller's own published rates and carry the date we last read them.

Which route should you take

Each row is the table above read for one question, at the unit named beside the price. Rows marked our call are editorial judgement instead, and appear only where we have something specific to say.

Provider board

Each column is one unit, and every price in it buys the same thing. The figures quoted elsewhere on this page are 1M output tokens. That is a baseline for comparing providers, not a quote. What you are actually billed depends on the settings you send, and on some routes on how much you top up at once. Every figure is the provider's own published price; anything we derived rather than read off a price list is marked est.

1 provider tracked · sorted by status, then price
ProviderAccess1M out1M incached inputcache writeStatus
First-party API
official$30.00claimed$5.00claimed$0.50claimed$6.25claimedlive · rate changes above 272K input

Swipe the table for price and status →

Seller terms not in the figures

Things that change what you pay without changing a price on this board. None of them is applied to the figures above: what one unit costs at the posted rate is a number anyone can check, and what it costs after a bonus depends on how much you buy at once.

OpenAI API · term
Prompts with more than 272K input tokens are priced at 2x input and 1.5x output for the whole request. Every figure on this row is the rate below that threshold. platform.openai.com
OpenAI API · term
Cache writes are billed at 1.25x the uncached input rate, which is where the $6.25 figure comes from. platform.openai.com

How these prices were read

How each figure above was read off the provider's own price list, and what that price list does not say.

OpenAI API
OpenAI publishes two rate cards for this model and a threshold between them. The figures here are the short-context card, which is what applies below the threshold; the long-context card is recorded as a term rather than as a second set of prices, because it is the same units at a multiplier and not a different thing to buy. Batch and Flex rates are published on their own tabs and have not been read.

Reference workload

This is not a price OpenAI publishes, and not a measurement of anything. It is a fixed reference scenario, 100K input + 20K output tokens, costed at the rates below and added up, so that models can be compared at one scenario instead of at whichever rate each one looks best on. The mix is ours and is not a claim about what a typical request looks like: change it and every figure here moves. The published rates are in the table under it, unchanged.

Reference scenario: 100K input + 20K output tokens, at the standard rate class
ProviderReference workload
OpenAI API$1.10derived
summed from rates the seller publishes · claimed

What it can do

Context window
1,050,000
Max output tokens
128,000
Accepts images
yes
Calls tools
not verified
Languages
not verified

Where a row says not verified, we have not checked that figure yet; it does not mean the model lacks the feature. Every row is read off published documentation for the model, never from our own testing.

If this is not the right model

Priced at the same unit

Claude Opus 5 Claude Sonnet 5 Claude Haiku 4.5

These sell 100K input + 20K output tokens too, so their figures on the index can be read against this one. Models that do not are shown with their own unit instead.