GPT-6.1 Sol API: Pricing, Specs, and How to Use It in Codex

Short answer

GPT-6.1 Sol (gpt-6.1-sol) is the mid-tier GPT-6 model OpenAI released on September 29, 2026. OpenAI positions it as "near-Astra performance for complex work at a lower cost": it is the model to pick when GPT-6 Astra is too expensive for everyday coding and GPT-6 Luna is not strong enough. The official price is $2 per million input tokens and $10 per million output tokens, with a 1.05M-token context window. On TeamoRouter it is available under the same model ID at roughly 20–30% of the official price (the live price is on the model page), and works in Codex CLI by changing two lines in config.toml.

Specs at a glance

From OpenAI's model page:

Since October 8 it also has an Ultrafast mode in the Responses API (service_tier: "ultrafast"), priced at 6x the standard rate.

Sol, Astra, or Luna

OpenAI's own guidance: start with GPT-6 Astra for the hardest reasoning and coding, choose GPT-6.1 Sol to balance intelligence and cost, and use GPT-6 Luna for cost-sensitive, high-volume work.

GPT-6.1 Sol vs GPT-6 Sol. The official input and output prices are the same, so for new work there is little reason to stay on gpt-6-sol. Cached input costs a twentieth of fresh input ($0.10 vs $2 per million at list), which matters in Codex, where most of each request is repeated context. Codex does not switch models by itself: if your config.toml says gpt-6-sol, change it by hand.

Pricing

Prompts above 272K input tokens are billed at 2x input and 1.5x output for the whole request. TeamoRouter bills the same tokens at roughly 20–30% of these list prices; prices change with supply, and the current numbers are on the GPT-6.1 Sol model page.

Use it in Codex CLI

Put this in ~/.codex/config.toml and set your TeamoRouter key in OPENAI_API_KEY:

model_provider = "teamorouter"
model = "gpt-6.1-sol"
model_reasoning_effort = "medium"

[model_providers.teamorouter]
name = "TeamoRouter"
base_url = "https://api.teamorouter.vip/v1"
env_key = "OPENAI_API_KEY"
wire_api = "responses"

medium is OpenAI's default effort and is enough for routine edits; raise it to high or xhigh for a hard refactor. Inside a session, /model switches between gpt-6.1-sol, gpt-6-astra and gpt-6-luna. Step-by-step setup: Codex CLI guide.

Call the API directly

Responses API (use this one if you need tool calling):

curl https://api.teamorouter.vip/v1/responses \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6.1-sol",
    "reasoning": {"effort": "medium"},
    "input": "Write a migration that adds an email column to the users table"
  }'

OpenAI Python SDK:

from openai import OpenAI

client = OpenAI(base_url="https://api.teamorouter.vip/v1", api_key="YOUR_KEY")
resp = client.responses.create(model="gpt-6.1-sol", input="Find the bug in this function: ...")
print(resp.output_text)

Chat Completions also accepts gpt-6.1-sol, but OpenAI does not support tool calling on that endpoint for this model. Full reference: API integration.

Paying for usage

No subscription: you top up a balance from $5 and pay only for the tokens you use, by card. The same key also works for Claude and Gemini.

FAQ

Is GPT-6.1 Sol better than GPT-6 Sol? OpenAI lists GPT-6.1 Sol as the current Sol model and describes it as near-Astra performance at a lower cost; at the same official price there is no reason to start new work on gpt-6-sol.

Which reasoning effort should I use? medium is the default. none and minimal are not supported on this model; xhigh and max cost more tokens and time and are worth it only for hard problems.

Does it accept images? Yes, text and image input; output is text only.

Codex says the model was not found. Check that config.toml has model_provider = "teamorouter" at the top and that OPENAI_API_KEY is set in the terminal that launched Codex.

Related

• GPT-6 Sol API: the previous Sol model and the Sol / Astra / Luna lineup
• GPT-6 Luna API: the cheapest GPT-6 model
• GPT-6 Astra pricing