How much does the GPT-5.6 Terra API cost?

On FastMetal, GPT-5.6 Terra is billed per token: $2.11 per 1M input tokens and $12.66 per 1M output tokens on a US-dollar account, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.

Can I call GPT-5.6 Terra with the OpenAI SDK?

Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "gpt-5.6-terra" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.

What is the context window of GPT-5.6 Terra?

1,050,000 tokens, shared between the prompt and the response.

What do I need to try GPT-5.6 Terra?

Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.

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OpenAI

gpt-5.6-terra

GPT-5.6 Terra

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic...

7/9/2026

1,050,000 tokens

Input: $2.11/M

Output: $12.66/M

Try in Chat Get API Key

Specifications

Modalities

Input

file

image

text

Output

text

Supported Parameters

include_reasoning

max_completion_tokens

max_tokens

reasoning

reasoning_effort

response_format

seed

structured_outputs

tool_choice

tools

Max Output Tokens

128,000

Reasoning Configuration

Default: Thinking on (effort: medium)
Selectable effort levels: max
xhigh
high
medium
low
none
Turning thinking off: Possible (reasoning.enabled: false)

How to control thinking, and what it costs

Data policy

Prompt retention: Unknown — we could not confirm
Training: Not used for training

"Unknown" does not mean "safe". It means we could not confirm it.

Whether a provider trains on prompts is a declared value from our terms with them. Retention is determined from the upstream listing for every host this model can reach. Neither is guessed.

Measured performance

Time to first response (p50)937ms

Throughput (p50)192 tokens/s

Measured through FastMetal's own gateway over the last 30 days (654 first-response samples).

Throughput is sampled once a day: the median of 26 observations over the last 30 days.

Time to first response is measured to the first streamed chunk; throughput counts all output tokens, including reasoning tokens. These are observations, not a performance guarantee.

Code Examples

curl https://api.fastmetal.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-5.6-terra",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

How GPT-5.6 Terra actually answers

Real responses to our standard prompts, recorded on FastMetal.

Count the number of 'r's in 'strawberry'

Count the number of 'r's in 'strawberry'. Explain your reasoning step by step.

“strawberry” is spelled: s t **r** a w b e **r** **r** y There are **3** occurrences of the letter **r**.

3.6s response71 output tokens

Debug This Error

I'm getting the following error in my Node.js application: TypeError: Cannot read properties of undefined (reading 'map') at UserList (/app/components/UserList.js:12:25) at renderWithHooks (/app/node_modules/rea…

The error means `users` is `undefined` when `UserList` renders, so React tries to evaluate: ```js users.map(...) ``` But `.map()` only exists on arrays. Common causes: - The parent component does not pass a `users` prop. - The user data is loaded asynchronously and has not arrived on the first render. - The API response shape differs from what you expect, e.g. data is in `response.data.users` rather than `response.data`. - The parent initializes its user state as `undefined` or `null`. ## Fix options ### 1. Initialize users as an empty array In the parent component: ```jsx const [users, setUsers] = useState([]); ``` Then pass it normally: ```jsx <UserList users={users} /> ``` An e…

5.8s response559 output tokens

Code Review

Please review the following Python function and suggest improvements for readability, performance, and best practices: def get_data(url, retries=3): import requests import time for i in range(retries):…

Here are the main areas to improve: ### Issues in the original code - **Imports inside the function**: Move `requests` and `time` imports to module scope. - **Bare `except:`**: This catches everything, including `KeyboardInterrupt` and programming errors. Catch `requests.RequestException` (and possibly JSON decoding errors) instead. - **Status code check**: Prefer `response.raise_for_status()` or `response.ok` over manually checking only for `200`. Successful responses can include other 2xx status codes. - **`== True`**: Use `if item.get("active"):` instead. - **Potential `KeyError`**: `item["name"]`, `item["id"]`, and `item["active"]` can fail if the API response is incomplete. Use `.get(…

10.6s response939 output tokens

Compare these answers side by side with other models →

Frequently asked questions

How much does the GPT-5.6 Terra API cost?: On FastMetal, GPT-5.6 Terra is billed per token: $2.11 per 1M input tokens and $12.66 per 1M output tokens on a US-dollar account, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.
Can I call GPT-5.6 Terra with the OpenAI SDK?: Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "gpt-5.6-terra" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.
What is the context window of GPT-5.6 Terra?: 1,050,000 tokens, shared between the prompt and the response.
What do I need to try GPT-5.6 Terra?: Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.