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BenchLM

Data as of September 30, 2026 · How the score is built

TrackedOpen WeightNon-Reasoning

N/A contextOpenAI model documentation

Whisper large-v3-turbo

Decision readingWhisper large-v3-turbo is tracked, but not publicly ranked yet. Published speech or voice results from Phonon-2 launch evaluation appear below. They do not produce a weighted text-model score.

Voice benchmark evidence

Phonon-2 launch evaluation is an owner-defined voice evaluation. Its result stays separate from BenchLM's weighted text-model ranking.

Seven-set mean WER
6.58%
LibriSpeech clean WER
2.13%
LibriSpeech other WER
3.71%
AMI WER
13.88%
Earnings-22 WER
8.09%
GigaSpeech WER
8.47%
SPGISpeech WER
2.79%
VoxPopuli WER
7.02%
Download
1,618 MB
whisper.cpp, large-v3-turbo (Metal)
17.0x realtime on M5 MacBook Air
Leaderboard row quoted by Fermion; Fermion launch table retrieved September 30, 2026. Lower WER is better; throughput excludes model load.

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Release date not sourced · you are here

    Whisper large-v3-turbo

    Not publicly ranked · Price not listed

Base entry

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Not publishedOpenAI model documentation
Context window
N/A
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Open multilingual speech recognition weights under MIT. The official model card documents a faster version of Whisper large-v3 with four decoder layers and inference through Transformers.
Cloud regions
Not tracked yet
Lifecycle
Tracked
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing recordOpenAI model documentation
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

We track Whisper large-v3-turbo, but no weighted text-model benchmark result is published on the site yet. This page shows the metadata and separate protocol evidence we can verify now; a BenchLM score will appear only if compatible public evaluations land.

Whisper large-v3-turbo is a open weight model with a N/A context window. No explicit reasoning mode is documented in this profile.

Open multilingual speech recognition weights under MIT. The official model card documents a faster version of Whisper large-v3 with four decoder layers and inference through Transformers.

Whisper large-v3-turbo is tracked with speech recognition results from Fermion's Phonon-2 launch evaluation. These results are display-only and stay separate from weighted text-model rankings.

Speech or voice evidence appears above; text-model benchmark coverage remains empty.

Last updated September 30, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Questions

How does Whisper large-v3-turbo perform overall in AI benchmarks?

Whisper large-v3-turbo has published speech or voice results in Phonon-2 launch evaluation. Those results remain separate from the weighted text-model ranking, so this profile does not assign a BenchLM score or overall rank. Use the linked evaluation's metric and run conditions to compare speech systems.

Is Whisper large-v3-turbo open source?

Whisper large-v3-turbo is an open-weight model from OpenAI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Does Whisper large-v3-turbo have full benchmark coverage on BenchLM?

No. Whisper large-v3-turbo's speech or voice results appear in Phonon-2 launch evaluation, but it has no published text-model benchmark rows. The voice evaluation does not fill the text-model coverage slots or produce an overall rank. Missing text coverage is not treated as a zero score.

What is the context window size of Whisper large-v3-turbo?

Whisper large-v3-turbo has a reported context window of N/A in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.

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