Jais-ASR released
IFM · Model release
Source confirmed
Data as of October 15, 2026 · How the score is built
CurrentOpen WeightNon-Reasoning
Released October 2026N/A contextIFM model documentation
Jais-ASR
Decision readingJais-ASR is tracked, but not publicly ranked yet. Published speech or voice results from Jais-ASR Arabic speech evaluation appear below. They do not produce a weighted text-model score.
Released October 2026 — see all recent releases
Jais-ASR will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Voice benchmark evidence
Jais-ASR Arabic speech evaluation is an owner-defined voice evaluation. Its result stays separate from BenchLM's weighted text-model ranking.
Six-set Arabic macro-average WER
22.85%
Six-set Arabic macro-average CER
8.37%
Mixat code-switched WER
17.8%
Mixat code-switched CER
6.0%
IFM evaluation retrieved October 15, 2026. Lower error rates are better. Six-set Arabic macro-averages and Mixat code-switched results are separate protocols; neither enters general model rankings.
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.
Base entry
Radar
Full release historyJais-ASR release history
Radar confirmed these at the source. Use Jais-ASR in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- Weights model ID
- IFM/Jais-ASRIFM model card
- Context window
- N/A
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- audioIFM model card
- Output modalities
- textIFM model card
- Parameters
- Not sourced yet
- Availability
- Hugging Face · self-hosted inferenceIFM model card
- Cloud regions
- Not tracked yet
- Lifecycle
- activeIFM model card
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordIFM 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 Jais-ASR, 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.
Jais-ASR is a open weight model with a N/A context window. No explicit reasoning mode is documented in this profile.
Apache 2.0 speech recognition weights built on a Jais-3 language backbone, with 11.4 GB BF16 weights. The model supports Modern Standard Arabic and dialects across 19 Arab countries, plus English, French, Spanish, and Italian. IFM supplies Transformers examples and a vLLM transcription plugin. The launch blog establishes October 2026, without an exact day.
Jais-ASR is an Arabic speech recognition model with code-switching, optional diacritization, and language and dialect identification. Its provider-reported speech results stay separate from text-model rankings.
Speech or voice evidence appears above; text-model benchmark coverage remains empty.
Last updated October 15, 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 parametersQuestions
How does Jais-ASR perform overall in AI benchmarks?
Jais-ASR has published speech or voice results in Jais-ASR Arabic speech 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 Jais-ASR open source?
Jais-ASR is an open-weight model from IFM. 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 Jais-ASR have full benchmark coverage on BenchLM?
No. Jais-ASR's speech or voice results appear in Jais-ASR Arabic speech 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 Jais-ASR?
Jais-ASR 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.