Gemma 4 26B API
Google's latest MoE model. Fast and efficient for everyday chat, summarization, and Q&A.
Provider: Google | Model ID: gemma-4-26b | Context Window: 256K tokens
On this model: 256K tokens context window, chat workload class, routed through Google infrastructure.
Pricing
₹10/1M input · ₹50/1M output. Pay-as-you-go micro-metered billing. UPI and cards accepted with zero minimum commitment.
| Token Type | Price (INR) |
|---|---|
| Input Tokens | ₹10/1M tokens |
| Output Tokens | ₹50/1M tokens |
| Prompt Caching Input | Standard input rate |
OpenAI-Compatible Integration
Drop into existing OpenAI SDK code by changing the base URL to https://api.luminoai.co.in/v1. The request shape below is the chat and general purpose pattern.
curl https://api.luminoai.co.in/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $LUMINO_API_KEY" \
-d '{
"model": "gemma-4-26b",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Summarise this document in five bullet points."}
]
}'
Why chat volume is predictable to budget
Chat workloads have short, stable output. That makes per-call cost easy to forecast: input tokens times the document size, output tokens times the reply length. The main leak is retries and regenerate buttons, which bill as fresh requests.
Model Specifications
| Model Identifier | gemma-4-26b |
|---|---|
| Provider | |
| Category | chat |
| Context Window | 256K tokens |
| Output Pricing Tier | budget |
| API Protocol | OpenAI-compatible REST API (JSON) |
| Endpoint | https://api.luminoai.co.in/v1/chat/completions |
Good fit for chat and general purpose
- Chat assistants and customer-facing support drafting
- Summarisation, extraction, and classification at volume
- Style and tone rewriting for content pipelines
- Any high-volume task where cost per call is the binding constraint
Gemma 4 26B API FAQ
How much does Gemma 4 26B cost per call?
Multiply your input tokens by the input rate and your reply length by the output rate. Both rates are in the pricing table above.
Is Gemma 4 26B good enough for production support?
For drafting, summarising, and structured extraction, yes. Keep a human in the loop for anything that commits money or changes account state.
How do I control spend on a chat product?
Cap max_tokens, rate-limit the regenerate button, and cache a stable system prompt.
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