GPT-5.6 Sol
verified model reference.

GPT 5.6 / EXACT-MATCH SEARCH ANSWERS

What is GPT-5.6 Sol? Specs, context window, reasoning and availability.

GPT-5.6 Sol is OpenAI's GPT-5.6 flagship model released on July 9, 2026. The API identifier is gpt-5.6-sol, with gpt-5.6 listed as an alias. Its 1,050,000-token context window and 128,000 output-token limit are separate serving capacities, not guaranteed retrieval accuracy. It accepts text and image input and generates text output.

The supported reasoning effort settings are none, low, medium, high, xhigh and max, with medium the default. The knowledge cutoff is February 16, 2026. The Responses API supports structured outputs, function calling and documented tools such as web/file search, code interpreter, hosted shell, apply patch and computer use, depending on account and tool settings.

Primary verification: OpenAI model card and OpenAI July 2026 launch report.

GPT-5.6 SOL API PRICING / USD PER 1M TOKENS

How much does GPT-5.6 Sol cost for input, output and prompt caching?

As of November 10, 2026, published Standard short-context text rates are $4 uncached input, $0.4 cached reads and $20 generated output per million tokens. Cache writes have two published rates: $5 for a 30-minute write and $10 for a 12-hour write. Promotional rates are shown through November 30, 2026; prices thereafter are not assumed.

The long-context threshold is strictly greater than 272,000 input tokens; input and cache rates double, and output rates rise 1.5× for the entire request. Cached reads are not the same as writes, and identical-looking prompts do not guarantee a cache hit. These figures omit tool-use charges, processing-mode changes, regional fees and any costs not represented in text-token rates.

Check the current OpenAI pricing table and prompt-caching guide before budgeting real deployments.

SXF INTERACTIVE RESEARCH TOOL / NO NETWORK REQUESTS

GPT-5.6 Sol cache calculator: 30-minute vs 12-hour cost.

Enter a repeated input prefix, fresh tokens per request, output tokens and the number of calls. The calculator models one initial cache write, then successful reads for subsequent requests, all within the chosen retention period. It automatically adjusts prices above 272K total input tokens. Your inputs stay in this browser.

SEARCHER COMPARISON / 5.6 SOL VS 6 SOL VS 6.1 SOL

GPT-5.6 Sol vs GPT-6 Sol vs GPT-6.1 Sol: what's actually different?

The models use distinct, versioned API IDs: gpt-5.6-sol, gpt-6-sol and gpt-6.1-sol. The query “5.6 Sol vs 6.1 Sol” is a cross-generation comparison, not a model alias. All three list a 1,050,000-token context limit, yet serving limits do not prove equal reasoning or coding accuracy. In particular, GPT-6.1 Sol does not offer reasoning.effort=none, unlike GPT-5.6 Sol and GPT-6 Sol.

* GPT-5.6 Sol Standard rates are promotional through November 30, 2026. For model migration, compare results on held-out representative tasks plus cost per accepted outcome. A newer release and lower input cost do not prove a specific performance gain.

Also see the direct GPT-5.6 vs GPT-6 comparison, GPT-5.6 family guide, GPT-6 family guide and SXF model pricing.

LAUNCH BENCHMARK EVIDENCE / PROVIDER-REPORTED

GPT-5.6 Sol benchmarks: coding, computer use and research.

OpenAI's July 2026 launch evaluation tables report scores for specific harnesses and model settings. These are vendor-reported results, not independently replicated SXF inference tests. The scores are deliberately not combined into a single universal intelligence rating.

Interpretation: these scores can help select tasks worth piloting, but cannot predict accuracy, latency or security for your deployment. Compare like-for-like test versions and allowed tools. See SXF evaluations for separately labelled benchmark records.

DIRECT API SETUP / DEVELOPER EXAMPLE

How to call GPT-5.6 Sol with the OpenAI Responses API.

Use the exact model ID gpt-5.6-sol and select a documented reasoning setting. The example below is an illustrative API request, not a live paid inference executed by SXF. Keep credentials in environment variables; never publish them in browser JavaScript or your Git repository.

from openai import OpenAI

client = OpenAI()  # reads OPENAI_API_KEY securely
response = client.responses.create(
    model="gpt-5.6-sol",
    reasoning={"effort": "medium"},
    input="Audit this Python patch. Explain risks and propose tests."
)
print(response.output_text)

Evidence-first evaluation checklist

1. Create a held-out, representative task set with clear acceptance criteria and negative controls.
2. Record exact prompt version, model ID, reasoning effort, available tools and tool outputs.
3. Measure accepted results, errors, human corrections, latency, billed input and output, cache writes/reads and retry count.
4. Repeat with GPT-6 Sol or GPT-6.1 Sol, keeping evaluation configuration comparable; calculate cost per accepted task.

Read the official API model card and prompt caching guidance for supported requests and caching rules.

SEARCH QUERY ANSWERS / FAQ

GPT-5.6 Sol frequently asked questions.

ORIGINAL DATA / METHODOLOGY / CORRECTIONS

How SXF reproduced the 20-case pricing study.

The experiment crosses prefix sizes 10K, 100K, 260K and 300K with call counts of 1, 2, 3, 10 and 100. Each call adds 2,000 fresh input tokens and 4,000 output tokens. For uncached requests the whole prefix is billed as new input each time. For cache scenarios the first call writes the prefix for 30 minutes or 12 hours; subsequent calls read the prefix from cache. All cache writes and reads are hypothetical billable events, assuming cache eligibility and successful reuse within retention time.

Each call uses Standard published unit rates. Above 272,000 total input tokens, input/cache rates double and output rates increase by 1.5× across the entire call. The pricing engine reads SXF's primary-source-backed canonical model ledger; 12-hour writes are twice the 30-minute write price, as specified on the official OpenAI pricing table. OpenAI's advertised $4/$20 rates are promotional through November 30, 2026, so this is a dated study, not a forward price guarantee.

The complete public CSV dataset contains the exact counts and modelled total costs. CI checks all 20 scenarios against the versioned catalog. This study does not measure cache-hit probability, API latency, task accuracy or model benchmark performance, and it excludes fees for tools, non-Standard processing and regional processing.

• OpenAI GPT-5.6 Sol model card: ID, alias, 1.05M context, output ceiling, reasoning and promotional period
• OpenAI API pricing: Standard rates, 30-minute/12-hour cache writes and long-context tiers
• OpenAI prompt caching guide: eligibility, reuse and retention
• OpenAI GPT-5.6 release report: July 2026 announcement and attributed benchmarks
• GPT-6 Sol model card and GPT-6.1 Sol model card: model comparison facts
• SXF original 20-case dataset: auditable token counts and calculated costs

SXF / AI independent calculation study, published November 10, 2026. Provider benchmark figures are explicitly attributed. Source corrections: SXF editorial policy and contact. Structured data reflects visible page content and does not promise search ranking or FAQ rich results.