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  • 1M context
  • Multimodal
  • Reasoning
  • Responses API
  • NEW · Oct 26

GPT-6.1 Terra on QuickSilver Pro

gpt-6.1-terra
OpenAILive availability—

GPT-6.1 Terra through one OpenAI-compatible API. Supported features: text input, text output, image input, streaming, reasoning, tool calling and JSON Schema.

  • 1M context
  • 128K max output
  • Vision
  • Tools
  • Reasoning · on by default
  • Streaming
  • JSON Schema output

You pay · input / output per 1M

$1.00 / $5.00

Prompts over 200K tokens: $2.00 / $7.50

OpenAI list source: openai.com/api/pricing

At a glance

Context
1M tokens
Input / 1M
$1.00
Output / 1M
$5.00
Thinks by default
Yes
Max output
128K
Latency · live
—

Everyday agentic coding, writing and screenshot understanding.

When is GPT-6.1 Terra the right call?

Curated from catalog capabilities and published prices, not a benchmark.

When to use

Use GPT-6.1 Terra when your application needs these capabilities: text input, text output, image input, streaming, reasoning, tool calling and JSON Schema.

  • Long documents and codebases, up to 1M tokens of context
  • Agents that call tools, with strict JSON Schema output
  • Prompts that include images
  • Multi-step reasoning, on by default

When to use something else

Choose a different model if your workflow requires capabilities beyond those listed here. Test your workload before committing to a model.

Compare alternatives in Models

Quickstart (curl)

Get an API key →
curl https://api.quicksilverpro.io/v1/chat/completions \
  -H "Authorization: Bearer $QSP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6.1-terra",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.quicksilverpro.io/v1",
    api_key=os.environ["QSP_KEY"],
)
response = client.chat.completions.create(
    model="gpt-6.1-terra",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.quicksilverpro.io/v1",
  apiKey: process.env.QSP_KEY,
});
const response = await client.chat.completions.create({
  model: "gpt-6.1-terra",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);
curl https://api.quicksilverpro.io/v1/responses \
  -H "Authorization: Bearer $QSP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-6.1-terra",
    "input": "Hello!"
  }'
python (OpenAI SDK)
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.quicksilverpro.io/v1",
    api_key=os.environ["QSP_KEY"],
)
response = client.chat.completions.create(
    model="gpt-6.1-terra",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

OpenAI-compatible. One-line migration via base_url.

Gateway behavior

Compatibility notes for this model.

prompt
Prompts up to 1M tokens. Above 200K prompt tokens the request bills at $2.00 input / $7.50 output per 1M.
max_tokens
Up to 128K output tokens.
  • /v1/chat/completions: Supported
  • /v1/responses: Supported
  • streaming: Supported
  • tools: Supported
  • image input: Supported
  • JSON Schema: Supported
  • reasoning: Supported

Where the price comes from

Catalog v70 · long-context tier above 200K prompt tokens

Provider reference
No provider list price is compared for this model.openai.com/api/pricing
Catalog verified
Prompt cache · not compared
$0.10 read · $1.25 5m write
Long-context tier
$2.00 / $7.50 over 200K

usage.cost = prompt_tokens × $1.00/1M + completion_tokens × $5.00/1M

/pricing.json

Base rates; cached prompt tokens bill at the cache rates above.

FAQ

Common questions

$1.00 input / $5.00 output per million tokens.

GPT-6.1 Terra

Try GPT-6.1 Terra with double credits — up to $50 in bonus credits

Get API Key

$1.00 / $5.00in / out per 1M tokens

TryGet API Key