LLM Reference

Gemini 3.5 Transcribe

Released
2026-08-26
Last refreshed
2026-09-02
Status
Researched today
ProprietaryCommercial use: conditionalAudio

Gemini 3.5 Transcribe is worth evaluating for general LLM work when its provider route and context window match the workload.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 98k context window
  • Buyers comparing 2 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Released
2026-08-26
Context
98k
Max output
32,768
Knowledge cutoff
2025-01
Specialization
speech-recognition
Openness
Proprietary
License
ProprietaryCommercial use: conditional
Weights
Not released
Code
Unknown
Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website
Pricing
Output / 1M
$12.00
Input / 1M
-

Cheapest of 2 routes · GCP Vertex AI

About

Gemini 3.5 Transcribe is Google DeepMind's speech-to-text model for audio files. Use gemini-3.5-transcribe for pre-recorded recordings when speaker diarization and word-level timestamps matter; use its documented gemini-3.5-transcribe-live access endpoint through the Live API for continuous, bidirectional streaming transcription. The model accepts audio and text within a 96K-token context and returns text with up to 32K output tokens.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

Compare all 2

Compare API pricing across 2 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
GCP Vertex AI-$12.00
ServerlessPartial
Google AI Studio-$12.00
ServerlessPartial

Available via routers & gateways(13)

Capabilities

Audio

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
Artificial Analysis ASR WER2.6AA-WER; non-streaming/batch; result as of August 2026Observed 2026-08-26
Confidence: confirmed
Notes: Recommended seed value: 2.6 WER (%; lower is better). Evaluator: Artificial Analysis. Harness/methodology: Google reports locally evaluating default competitor APIs; Artificial Analysis' AA-WER index spans diverse datasets and separately evaluates non-streaming and streaming modalities. This row is for gemini-3.5-transcribe only, not the Live endpoint.
Source

Migration checks

No linked migration route is available for this model yet.

API versions

gemini-3.5-transcribegemini-3.5-transcribe-live