Gemini 3.5 Live Translate

Gemini 3.5 Live Translate by Google AI: $3.50 input and $21 output per 1M tokens, 16K context. Call it through the odnoga LLM gateway.

Streaming

Gemini 3.5 Live Translate is served by Google AI and called through odnoga with the same OpenAI-compatible request shape as every other model in the catalog. Its 16K-token context window sets how much input you can send in one request.

Specification and price

VendorGoogle AI
Model IDgemini-3.5-live-translate-preview
Context window16K tokens
Max output33K tokens
CapabilitiesStreaming
Your plan
Per 1M tokensVendor costYour price on Free+7%
Input$3.50$3.76
Output$21$22.58
Cached input

Vendor cost is the list price per million tokens as recorded in the odnoga catalog; your price applies your plan margin with the same formula that bills every request — see pricing. Pricing

Call it through odnoga

const res = await fetch("https://api.odnoga.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.ODNOGA_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "gemini-3.5-live-translate-preview",
    messages: [{ role: "user", content: "Hello" }],
  }),
});

Same request shape for every vendor in the catalog — swap the model id and odnoga handles keys, routing, limits and cost accounting.

How to use Gemini 3.5 Live Translate

Derived from the odnoga catalog record for this model.

Best for

  • High-volume, latency-sensitive calls: classification, extraction, routing, short rewrites and summaries.
  • User-facing chat where partial output should appear while the model is still writing.

Not the right pick when

  • Anything that needs to read an image — this model takes text only.
  • Agent loops that must call your functions — tool calling is not available here.
  • Pipelines that require guaranteed JSON — parse defensively or pick a model with enforced JSON.
  • Large documents in one request — the window is 16K tokens, so you will need chunking.
  • Anything where a wrong answer is costly without a human check — no model in the catalog removes that requirement.

Practical tips through odnoga

  1. 01Pin the model id in a managed prompt version, so a model swap is a version change you can compare and roll back, not an edit in application code.
  2. 02Compare it against 2–8 other models on the same frozen test cases in the evaluation laboratory before you make it the production default.
  3. 03For repeated identical deterministic calls, odnoga answer reuse returns the stored answer and bills no vendor tokens — turn it off for creative output.
  4. 04Set a fallback model on the route so a vendor incident degrades quality instead of returning an error, and a per-tenant budget so one caller cannot spend the month.

What a month costs

1,000 calls a month, 10,000 input tokens and 2,000 output tokens each, at your Free price (vendor cost +7%):

Input (10M tokens)$37.63
Output (2M tokens)$45.16
Your cost per month on Free$82.80

Vendor list cost $77.00 + odnoga margin $5.80 (+7%). Cached input or answer reuse lowers it; odnoga records both numbers per request.

Gemini 3.5 Live Translate compared

ModelContextInput / 1MOutput / 1MCapabilities
Gemini 3.5 Live Translate16K$3.50$21Streaming
Gemini 2.5 Computer Use131K$1$5Vision, Tools, JSON mode, Streaming
Gemini 2.5 Flash Image (Nano Banana)33K$0.3$2.50Vision

Questions

How much does Gemini 3.5 Live Translate cost per 1M tokens?
Google AI lists $3.50 / $21 per 1M input / output tokens in the odnoga catalog. Through odnoga you pay that vendor price plus your plan margin, and every request is recorded with both numbers.
What is Gemini 3.5 Live Translate best for?
High-volume, latency-sensitive calls: classification, extraction, routing, short rewrites and summaries. User-facing chat where partial output should appear while the model is still writing.
Can I switch to Gemini 3.5 Live Translate without changing my code?
Yes. odnoga exposes one OpenAI-compatible endpoint, so switching means sending "gemini-3.5-live-translate-preview" as the model id — or changing it in the managed prompt version, with no application deploy.
How large is the Gemini 3.5 Live Translate context window?
16K tokens of input, with up to 33K tokens of output per response.

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Where this model sits

One gateway, every model.