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 TypePrice (INR)
Input Tokens₹10/1M tokens
Output Tokens₹50/1M tokens
Prompt Caching InputStandard 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 Identifiergemma-4-26b
ProviderGoogle
Categorychat
Context Window256K tokens
Output Pricing Tierbudget
API ProtocolOpenAI-compatible REST API (JSON)
Endpointhttps://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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