gpt-5.6-terra
GPT-5.6 Terra — OpenAI's balanced tier of the GPT-5.6 family, sitting at the default reasoning effort. OpenAI-compatible /v1/chat/completions on api.reapi.ai with a 1,050,000-token context window, 128,000 max output tokens, six reasoning-effort rungs, and text plus image input.
OpenAI's GPT-5.6 Terra — the tier that balances intelligence and cost — exposed through api.reapi.ai as a drop-in
OpenAI-compatible Chat Completions endpoint. A 1,050,000-token context
window, 128,000 max output tokens, six reasoning_effort rungs from
none to max defaulting to medium, text and image input, and
functions, web search, file search and computer use. OpenAI rates its reasoning Higher and its speed Fast. The wire
model id is gpt-5.6-terra. Current rates live on the
model page and on
api.reapi.ai/pricing.
The URL and the model id differ. This page and the model page spell the slug
gpt-5-6-terra because a URL cannot carry dots. The string your request body needs is
gpt-5.6-terra.
Quick example
curl https://api.reapi.ai/v1/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5.6-terra",
"messages": [
{ "role": "user", "content": "Implement the change in the linked issue, with tests." }
],
"reasoning_effort": "medium",
"max_completion_tokens": 8192,
"stream": true
}'from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.reapi.ai/v1",
)
stream = client.chat.completions.create(
model="gpt-5.6-terra",
messages=[{"role": "user", "content": "Implement the change in the linked issue, with tests."}],
reasoning_effort="medium",
max_completion_tokens=8192,
stream=True,
)
for chunk in stream:
delta = chunk.choices[0].delta.content
if delta:
print(delta, end="")import OpenAI from "openai";
const client = new OpenAI({
apiKey: "YOUR_API_KEY",
baseURL: "https://api.reapi.ai/v1",
});
const stream = await client.chat.completions.create({
model: "gpt-5.6-terra",
messages: [{ role: "user", content: "Implement the change in the linked issue, with tests." }],
reasoning_effort: "medium",
max_completion_tokens: 8192,
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
body, _ := json.Marshal(map[string]any{
"model": "gpt-5.6-terra",
"messages": []map[string]string{
{"role": "user", "content": "Implement the change in the linked issue, with tests."},
},
"reasoning_effort": "medium",
"max_completion_tokens": 8192,
})
req, _ := http.NewRequest("POST",
"https://api.reapi.ai/v1/chat/completions", bytes.NewReader(body))
req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
req.Header.Set("Content-Type", "application/json")
resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()
out, _ := io.ReadAll(resp.Body)
fmt.Println(string(out))
}Authentication
Chat models are served from the api.reapi.ai gateway, which has its own console
and its own key. Create the key there, then send it as a bearer token:
Authorization: Bearer YOUR_API_KEYThe gateway key is not the same credential as a media-generation key used
against reapi.ai/api/v1. Sign in at
api.reapi.ai to create one.
Endpoint
POST /v1/chat/completionsBase URL https://api.reapi.ai. The wire format is OpenAI-compatible, so the
same SDKs work once you swap the base URL, the key and the model string.
OpenAI states that its reasoning models "work better with the Responses API",
and that "while the Chat Completions API is still supported, you'll get improved
model intelligence and performance by using Responses." The GPT-5.6 release entry
lists v1/responses, v1/chat/completions and v1/batch as this family's
endpoints — so Chat Completions is a documented, supported surface, and this is a
vendor preference rather than a restriction.
Request body
model — string, required
Must be gpt-5.6-terra exactly. There is no alias for this tier — the bare gpt-5.6 id routes to the frontier model instead.
messages — array, required
Conversation history, each entry an object with role and content. Roles are
system, user, assistant and tool. Text and image parts are supported —
see Image input.
max_completion_tokens — integer
Upper bound on generated tokens for this response, reasoning tokens included. The documented maximum output is 128,000 tokens.
Reasoning tokens bill as output tokens and occupy the context window. A budget sized only for the visible answer can truncate on a harder prompt, and it is the usual reason an invoice exceeds an estimate built from answer length.
reasoning_effort — string, default "medium"
How much the model thinks before answering. See Reasoning effort.
stream — boolean, default false
When true, tokens arrive as server-sent events terminated by data: [DONE].
At the default effort the model thinks before it answers, so streaming is what keeps an interactive surface from looking stalled.
tools / tool_choice — optional
Function definitions and the selection strategy. Functions, web search, file search and computer use are all available on this family, and this generation adds programmatic tool calling.
response_format — object, optional
Constrains the answer's shape, including a JSON schema for machine-consumed output.
group — string, default "default"
Token group on the gateway. Leave it at default unless your account has been
given another group to route through.
Reasoning effort
Six rungs, and unlike some families these do not collapse into one another —
each is a distinct behaviour. The default is medium: OpenAI's docs state
that "if you omit reasoning.effort, GPT-5.6 defaults to medium in both modes."
| Effort | OpenAI's stated best-for |
|---|---|
none | Latency-critical tasks that do not benefit from reasoning or multi-chained tool calls — voice, fast retrieval, classification |
low | Efficient reasoning with modest added latency: tool use, planning, search, multi-step decisions |
medium | Default. Quality and reliability where the task involves planning and judgement — agentic coding, research, spreadsheets and slides, delegated long-horizon work |
high | Hard reasoning, complex debugging, deep planning, high-value tasks where quality beats latency |
xhigh | Deep research and long asynchronous runs — security and code review, enterprise productivity. "Only use when your evals show a clear benefit" |
max | "Maximum reasoning for your most complex tasks. If you are currently using xhigh, evaluate if max results in stronger performance" |
There is no minimal on this family.
This tier is where the default is genuinely the right starting point. Sweep low
for speed on planning-shaped work and high when a route needs complex debugging;
if your evals keep choosing xhigh or max, that route belongs on the frontier
tier instead.
OpenAI also documents a Pro reasoning mode for GPT-5.6 (reasoning.mode,
independent of effort), and multi-agent orchestration in beta. Both are
features of OpenAI's Responses API, so neither is part of a Chat Completions
request through this endpoint.
Image input
| Modality | Supported |
|---|---|
| Text in | ✅ |
| Image in | ✅ |
| Text out | ✅ |
This generation accepts images at their original dimensions, with original
or auto image detail — no resizing step required before a screenshot or scan
goes in. Output is text only.
Pricing dimensions
Billing is per token, in USD, against your api.reapi.ai balance, with
separate input and output rates. Three things to keep in mind:
- Reasoning tokens bill as output. The default effort is
medium, so a request that omits the field is paying for a reasoning pass. - Effort is the first lever, and on this family every rung is real — a middle setting buys a middle cost.
- The tier is the second lever. All three GPT-5.6 tiers share this context window, this output ceiling, this effort ladder and this endpoint, so moving between them changes reasoning depth and price, not capability surface.
Both token rates sit 20% below OpenAI's published per-token rate, on input and output alike. Current numbers are on the model page and api.reapi.ai/pricing — those tables are the canonical source, not this page.
OpenAI prices cached input as a separate dimension. reAPI does not publish a cached-input rate for this model, so bill against the input and output rates in the pricing table.
Chat models bill in USD on the gateway balance. They do not draw down the
integer credits used by the media-generation endpoints on reapi.ai/api/v1.
Response shape
Non-streaming (stream: false)
{
"id": "chatcmpl-...",
"object": "chat.completion",
"created": 1785000000,
"model": "gpt-5.6-terra",
"choices": [
{
"index": 0,
"message": { "role": "assistant", "content": "..." },
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 1204,
"completion_tokens": 860,
"total_tokens": 2064
}
}usage.completion_tokens includes reasoning tokens, so it is the number to
reconcile a bill against. On OpenAI's own Responses API the split is reported
under output_tokens_details.reasoning_tokens.
Streaming (stream: true)
Server-sent events, each data: line carrying a chat.completion.chunk with the
incremental text in choices[0].delta.content, terminated by data: [DONE].
Errors
Failures use the gateway's standard envelope. See the errors catalog for the full code list. Common cases:
| Trigger | What to do |
|---|---|
| Missing or invalid bearer token | Create a key in the api.reapi.ai console |
Unknown model value | Send gpt-5.6-terra with the dots — not the hyphenated slug |
reasoning_effort set to minimal | Not a value on this family — use none, low, medium, high, xhigh or max |
reasoning.mode or multi-agent fields | Responses-API features; not part of a Chat Completions request |
max_completion_tokens above the ceiling | Lower it; the documented maximum output is 128,000 |
| Truncated answer on a hard prompt | The reasoning pass consumed the allowance — raise max_completion_tokens |
| Insufficient balance | Top up on the gateway |
| Upstream rate limit | Retry with backoff, or route through another tier |
Tips
- Leave the default alone first.
mediumis what OpenAI calls the well-balanced point, and this tier is priced for it. - Then sweep in both directions on a real route —
lowfor speed,highfor hard debugging — and keep whichever your evals prefer. - Escalate on evidence, not instinct. A route that always wants
xhighormaxis telling you it belongs one tier up. - Use a JSON schema for agent steps whose output another step consumes.
- Budget for the reasoning pass in
max_completion_tokens, not just the answer. - The window is the frontier tier's. Choosing this tier does not shrink what the model can see.
Related
- GPT-5.6 Terra model page — current rates
- GPT-5.6 Sol — the frontier tier above it
- GPT-5.6 Luna — the volume tier below it
- Errors catalog
- Authentication
- Quickstart