Gemini 3.5 Transcribe preview

Google Vertex AI audio transcription

Gemini 3.5 Transcribe preview is a Google Vertex AI speech-to-text model.Input is priced at $2.00/M tokens and output at $12.00/M tokens. Capabilities include audio input. Route Gemini 3.5 Transcribe preview via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: Oct 22, 2026 View source ↗
Cost calculator

Estimate Gemini 3.5 Transcribe preview spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
0200,000
400
016,000
5,000
01,000,000
Per request
$0.0108
in $0.006000 · out $0.004800
Per day
$54.00
5,000 requests
Per month
$1,644
152,188 requests

Estimate uses $2.00/M input · $12.00/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified Oct 22, 2026.

Input $2.00/M
Output $12.00/M
Blended (3:1 in:out) $4.50/M
Cross-model comparable price

Context & limits

Context window
—
Max input
—
Max output
—
Modalities
audio_in, audio, text

Capabilities

  • Function calling — not advertised
  • Parallel tool calls — not advertised
  • Vision input — not advertised
  • Audio input ✓ supported
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output — not advertised
  • Prompt caching — not advertised
  • Reasoning — not advertised

Strengths & caveats — when to pick Gemini 3.5 Transcribe preview

Data-driven from Gemini 3.5 Transcribe preview's percentile within audio transcription peers.

Where it's strong

  • +pricing — cheaper than 77% of priced audio transcription models on Future AGI
  • +audio input — only 17% of audio transcription models on Future AGI advertise this

Watch out for

  • No major caveats flagged from public spec.

Benchmarks pending

We haven't logged public benchmark scores for Gemini 3.5 Transcribe preview yet. Have one to contribute? Submit a source — citations help us prioritise.

Try it

Call Gemini 3.5 Transcribe preview via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# Gemini 3.5 Transcribe preview via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="vertex-ai/gemini-3-5-transcribe-preview",
    messages=[{"role": "user", "content": "Hello, Gemini 3.5 Transcribe preview!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="vertex-ai/gemini-3-5-transcribe-preview",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗

Explore similar models

Gemini 3.5 Transcribe preview doesn't have a public Arena ELO score yet, so we group by provider only — quality-tier comparisons need a benchmark. Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does Gemini 3.5 Transcribe preview cost?

Input is priced at $2.00 per 1M tokens and output at $12.00 per 1M tokens (Google Vertex AI, last verified Oct 22, 2026).

What is the context window of Gemini 3.5 Transcribe preview?

Context window for Gemini 3.5 Transcribe preview is not currently public.

Does Gemini 3.5 Transcribe preview support function calling?

Gemini 3.5 Transcribe preview does not currently advertise function-calling support. For agentic workloads, prefer a tool-calling-capable model and route via Agent Command Center for fallback.

Is Gemini 3.5 Transcribe preview good for production?

Gemini 3.5 Transcribe preview is well-suited for pricing — cheaper than 77% of priced audio transcription models on Future AGI and audio input — only 17% of audio transcription models on Future AGI advertise this.

How can I route to Gemini 3.5 Transcribe preview with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for Gemini 3.5 Transcribe preview

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.