LumeAPILong-context RAG
60M input + 6M output tokens / month
Large retrieved chunks
- Official (Gemini 3.1 Pro)
- $192.00/mo
- LumeAPI
- $115.20/mo
- Monthly savings
- $76.8040% off
Gemini Pro API
Gemini Pro API — Complex Reasoning, Coding & Long Context
Gemini 3.1 Pro at ~40% below reference for complex reasoning, coding, and long-context RAG.
Model id: gemini-3.1-pro-preview. Test 200K+ context and native features in staging.
- OpenAI-compatible
- Pay as you go
- One API key
- GPT, Claude & Gemini
Gemini 3.1 Pro pricing
Official reference vs LumeAPI catalog rates. Pricing unit: per 1M input / output tokens. Last updated: July 2026. Source: provider list price.
| Model | Official (in / out) | LumeAPI (in / out) | Savings | |
|---|---|---|---|---|
| Gemini 3.1 Progemini-3.1-pro-preview | $2.00 / $12.00 | $1.20 / $7.20 | 40% off | Details → |
Monthly cost examples
Illustrative totals for gemini-3.1-pro-preview using catalog list prices — your actual bill depends on retries, tool loops, and output length.
Complex coding
20M input + 8M output tokens / month
Pro vs Flash on hard tasks
- Official (Gemini 3.1 Pro)
- $136.00/mo
- LumeAPI
- $81.60/mo
- Monthly savings
- $54.4040% off
Pro and long-context economics
Gemini Pro API bills every token you send—including retrieved documents on every RAG query. A 60M input token month on Pro is a planning problem, not a surprise, when you model chunk size up front.
Thinking-token and very-long-context behavior should be validated in Usage logs on representative prompts. Official Google Batch may still win for offline jobs.
Pair this page with /rag-api when search intent is document Q&A cost control.
Integration checklist for Gemini Pro
RAG pipelines should measure average input tokens per query after retrieval. If inputs creep above plan, fix chunking before blaming the model tier.
Validate thinking-token or long-output behavior on a weekly sample of production prompts and adjust max_tokens defaults accordingly.
Self-serve path: register to first API call
LumeAPI is designed for developers who want to integrate without scheduling demos. Create an account, confirm your email, and open Console to generate an API key. Fund your USD wallet with USDT on supported chains when you are ready for billable traffic—there is no mandatory minimum beyond what your tests require.
Point your OpenAI-compatible client at https://api.lumeapi.site/v1, set Authorization to Bearer your key, and pass a catalog model id in the model field. Run a short curl or SDK script from /docs to verify latency, streaming, and error handling before you attach the key to production services.
Use Usage logs to reconcile per-call cost with finance forecasts. When a model tier is too expensive or quality is insufficient, change model id—not your entire integration. For cross-provider price tables and Research deep dives, follow internal links on this page rather than duplicating migration math here.
Documentation, catalog, and support
Every catalog model has a detail page under /models with official reference pricing, LumeAPI pricing, and links to /docs/models/{id} for parameters and curl examples. Start there when this commercial page points you to a model id you have not called before.
The /docs index lists gateway authentication, Chat Completions, image endpoints, and async video patterns. llms.txt bundles the same information for agent tooling—useful when you want a single URL to paste into Cursor or an internal bot.
Research articles explain why bills grow and how to compare providers; commercial pages like this one explain what LumeAPI offers and how to start. Follow internal links instead of searching for duplicate migration content across pages.
If billing, chain deposits, or integration behavior is unclear, use /contact for support channels. Include your model id, approximate request time, and whether the issue is authentication, balance, or model parameters—that speeds up resolution.
Why LumeAPI
Mainstream models only
GPT, Claude, and Gemini catalog ids with published per-token or per-media rates — not obscure small models marketed as discounts.
Transparent pricing
Official reference vs LumeAPI columns on every commercial page. Your request model id matches Usage logs and billing.
OpenAI-compatible gateway
One base URL for Chat Completions, image generations, and async video. Swap key, base URL, and model id — keep your SDK.
Self-serve wallet
Top up with USDT, create keys in Console, and track per-call cost in Usage — no sales calls required.
Get started in three steps
- Create an API key — register and open Console.
- Set the LumeAPI base URL — https://api.lumeapi.site/v1
- Choose a supported model id — from the table above or model catalog.
Migrate in minutes
Three values change: API key, base URL, model id. Everything else stays the same.
Before (official Google Gemini Pro)
from openai import OpenAI
client = OpenAI(api_key="YOUR_OPENAI_API_KEY")
response = client.chat.completions.create(
model="gemini-3.1-pro-preview",
messages=[{"role": "user", "content": "Hello"}],
)After (LumeAPI)
from openai import OpenAI
client = OpenAI(
api_key="YOUR_LUMEAPI_KEY",
base_url="https://api.lumeapi.site/v1",
)
response = client.chat.completions.create(
model="gemini-3.1-pro-preview",
messages=[{"role": "user", "content": "Hello"}],
)Full step-by-step rollout, streaming checks, and FAQ: Gemini cost guide →
Migration & compatibility
What changes
API key, base URL (https://api.lumeapi.site/v1), and model id to a LumeAPI catalog entry. Message shape stays OpenAI-compatible for most apps.
What to test
Streaming, tool calling, JSON mode, and error handling on your heaviest models. Shadow 5–10% of traffic before full cutover.
What may differ
Provider-native features (Anthropic Batch, Google Grounding, OpenAI Assistants) may require the official API. Test your exact payload.
Rollback
Keep environment variables for base URL and model id. Switch back instantly if staging tests fail.
Trust & billing
200K+ context?
Test payload size against model docs.
Thinking tokens?
Validate in Usage logs.
Google Batch?
Batch may win async. LumeAPI targets real-time.
Exact id?
gemini-3.1-pro-preview in billing.
Built for these workloads
Complex reasoning
Where Flash quality is insufficient.
Coding
Compare Pro vs GPT Terra and Claude Sonnet.
Long context
Input token cost dominates — lower rates help.
Multimodal text
Pro-class tasks before image pipelines.
Related guides
FAQ
Gemini Pro cost?
Input and output per 1M in table.
Pro vs Flash?
Flash for volume. Pro for quality and context.
RAG?
See /rag-api.
OpenAI SDK?
Yes on LumeAPI base URL.
Hub?
See /gemini-api.
Grounding?
May need native API — test first.
Call Gemini Pro on LumeAPI
Use gemini-3.1-pro-preview through https://api.lumeapi.site/v1. Need help choosing a model? Browse the developer docs or contact support.