GPT-6 Sol · reference-only

GPT-6 Sol Token Counter

Inspect text while planning GPT-6 Sol coding and agent requests. The local count is a reference encoding comparison; OpenAI supplies the model-aware input count.

Accuracy note

reference-only for GPT-6 Sol. No local Sol tokenizer mapping has been verified in this project. Reference token IDs are encoding-specific, and complete request usage must be checked with OpenAI.

Official counting docs →
API model ID
gpt-6-sol
Context
1,050,000 tokens
Maximum output
128,000 tokens
Local support
reference-only

Facts checked against official sources on .

What is GPT-6 Sol Token Counter?

This GPT-6 Sol token counter guide helps plan input for gpt-6-sol, a model intended for complex coding and agent workflows. Source files, conversation history and tool definitions can make an agent request much larger than the last user message alone.

The official Sol document lists a 1,050,000-token context window and 128,000 maximum output tokens. It also points to GPT-6.1 Sol as a newer model. This page covers the original gpt-6-sol ID so its counting guidance and price table remain tied to an explicit API model.

GPT-6 Sol Tokenizer Support in Tiktokenizer

Support level: reference-only. The project has no verified GPT-6 Sol mapping in its existing browser tokenizer runtime. o200k_base is offered as a reference text explorer, with live boundaries and IDs for that encoding only.

Exact support would require the named tokenizer to be verified; compatible support would require an established mapping. Reusing a GPT-5.6 option does not establish either for Sol. For a request-level input count, send your intended structured input to OpenAI's Responses input-token counting operation with model gpt-6-sol.

GPT-6 Sol Pricing and Cost Notes

Facts checked on 2026-10-08. Prices below are USD per 1M tokens for Standard processing with up to 272,000 input tokens, verified against the official GPT-6 Sol model document.

For prompts above 272,000 input tokens, the full request uses 2x input and cache rates and 1.5x output rates. Processing-tier discounts, Fast mode and regional premiums can change the applicable rate. Cached reads are priced at 10% of ordinary input at the same tier; writing a cache is a separate usage category.

Usage categoryUSD per 1M tokens
Input$2.00
Cache read$0.20
Cache write$2.50
Output$10.00

How to Count GPT-6 Sol Tokens

  • 1. Paste source text or a prompt into the reference explorer to inspect raw-encoding tokens and IDs locally.
  • 2. When preparing an agent request, gather the complete message history, system instructions, supported tools and media rather than counting only the newest prompt.
  • 3. Use OpenAI's Responses input-token count with model gpt-6-sol and the same structured payload you will send for generation.
  • 4. Reserve output capacity and compare the generated response's usage with the preflight input count. Use the correct processing tier when estimating cost; the browser does not call the model.

Token Count vs Billed Usage

The reference explorer cannot apply Sol's complete chat template, serialize an agent's tool schemas, count image inputs or reconstruct provider formatting. These components can alter input usage even when the visible user text has not changed.

Reasoning and generated output are determined during generation, while cache classification depends on provider state. Tool activity may incur fees beyond text-token pricing. A preflight input count helps plan the request; final usage and the applicable price categories determine its cost. Count every agent turn rather than treating one pasted prompt as the whole workflow.

Tiktokenizer Reference Sources

Tokenizer behavior and model limits change. Verify production decisions with current provider documentation:

Frequently asked questions

Is the local count exact for GPT-6 Sol?

No. Sol support is reference-only in this project. The selected raw encoding is useful for inspection but has not been verified as Sol's tokenizer.

Is GPT-6 Sol the same model as GPT-6.1 Sol?

No. They have distinct model IDs. This page's guidance and price table are tied to gpt-6-sol; check the document for the ID you actually call.

What are GPT-6 Sol's input and output prices?

As checked on 2026-10-08, Standard short-context prices are $2 input and $10 output per 1M tokens. Cache reads, writes and requests above 272,000 input tokens have separate rates.

Should I count all messages in a coding agent request?

Yes. Include the complete supported input, such as system instructions, history, tools and media, in OpenAI's model-aware counting operation. Inspect final usage for output, reasoning and cache categories.