Googleactive

Gemini 4 Argon

meldport/gemini-4-argon

Gemini 4 Argon is available through Meldport as gemini-4-argon. Published capabilities: Text, Vision, Cache, Stream, Tools.

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MODEL OVERVIEW

About Google Gemini 4 Argon

Gemini 4 Argon is available through Meldport as gemini-4-argon. Published capabilities: Text, Vision, Cache, Stream, Tools.

Use the published model ID in requests to Meldport's API. Check the current pricing, context window, and supported capabilities on this page before sending production traffic. See the quickstart for a request example.

GOOD FIT FOR

Text generation, extraction, and automation
Image-aware prompts and visual analysis
Tool calling and agent workflows

BEFORE YOU SHIP

Check capabilities, context limit, and price against your workload.
Test tool call parsing and error handling before production.
Verify image input size and format limits for your use case.

TECHNICAL SPECIFICATIONS

What this model supports

Model ID	`meldport/gemini-4-argon`
Publisher	Google
Capabilities	Text, Vision, Cache, Tools
Context window	1M
Lifecycle	active
Verified	Nov 1, 2026

CURRENT RATES

Pricing

Metric	Rate	Unit
Input	$0.6	per million tokens
Output	$3.6	per million tokens
Provider-reported cached input	$0.06	per million tokens
Minimum charge	$0.00001	per request

Provider-reported cached input tokens use the displayed rate. Every request is recorded in the wallet ledger.

QUICKSTART

Call this model

The same endpoint works from any language.

Send POST /v1/chat/completions with an API key that has inference:invoke. Use meldport/gemini-4-argon in the model field. Supply your conversation in messages and set stream: true for streamed output. The published context limit is 1M tokens.

This model publishes tool calling. Send function definitions in tools and return tool results in the conversation. Vision inputs are listed for this model. Request fields and output limits · Streaming format · Errors and retry rules

curl https://api.meldport.com/v1/chat/completions \
  -H "Authorization: Bearer $MELDPORT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meldport/gemini-4-argon",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

import os
import requests

response = requests.post(
    "https://api.meldport.com/v1/chat/completions",
    headers={
        "Authorization": f"Bearer {os.environ['MELDPORT_API_KEY']}",
    },
    json={
        "model": "meldport/gemini-4-argon",
        "messages": [{"role": "user", "content": "Hello"}],
    },
)
print(response.json())

const response = await fetch(
  "https://api.meldport.com/v1/chat/completions",
  {
    method: "POST",
    headers: {
      Authorization: "Bearer " + process.env.MELDPORT_API_KEY,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      model: "meldport/gemini-4-argon",
      messages: [{ role: "user", content: "Hello" }],
    }),
  },
);
console.log(await response.json());

COMMON QUESTIONS

Frequently asked questions

What is the API model ID for Gemini 4 Argon?

Use meldport/gemini-4-argon in the model field of your API request.

Which capabilities does Gemini 4 Argon support?

This model currently publishes Text, Vision, Cache, Tools support through Meldport.

How is Gemini 4 Argon priced?

Requests are billed per token. Input costs $0.6 per million tokens and output costs $3.6 per million tokens. Provider-reported cached input tokens cost $0.06 per million tokens; Meldport response caching is bypassed. A minimum charge of $0.00001 applies per request. Charges are deducted from your wallet balance in real time.

Which endpoint runs Gemini 4 Argon?

Send a request to POST https://api.meldport.com/v1/chat/completions with your Meldport API key and use meldport/gemini-4-argon in the model field.

What context window does Gemini 4 Argon support?

The published context limit is 1M tokens.