deepgram
Deepgram: Nova-3
deepgram/nova-3
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
Deepgram Nova-3 (canonical ID deepgram/nova-3-20260714) is listed in the OpenRouter catalog as a general-purpose speech-to-text model that accepts audio input and produces transcription output. The catalog description states that it supports both monolingual and multilingual transcription. No independent model card was available in this source pack, and the catalog entry reports no benchmark results, evaluation scores, or detailed feature list. Capabilities beyond the basic transcription modality, such as supported languages or streaming behavior, are not documented in the supplied evidence and should be verified before adoption.[1]
Strengths
Limitations
- Evidence is catalog-only: no independent model card, documentation, or measured performance data was available in this source pack.[1]
- The catalog reports no benchmark results or quality metrics, so transcription accuracy and latency must be validated on the target workload.[1]
- Details such as supported languages, streaming behavior, diarization, and configuration parameters are unspecified; absence of these fields means unknown, not unsupported.[1]
Where to use it
- Worth evaluating for general-purpose transcription pipelines, such as converting recorded calls or meetings to text, subject to accuracy testing on real audio.[1]
- Plausible candidate for multilingual transcription projects, though the specific language coverage is undocumented and needs confirmation.[1]
Sources
- [1] OpenRouter catalog · Deepgram: Nova-3Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Deepgram Nova-3 general-purpose speech-to-text model with monolingual and multilingual transcription support.
Specifications
- Model ID
- deepgram/nova-3
- Canonical ID
- deepgram/nova-3-20260714
- Creator
- deepgram
- Added to OpenRouter
- 15.07.2026
- Context length
- 0
- Modality
- audio->transcription
- Input modalities
- audio
- Output modalities
- transcription
- Token pricing
- No per-token price in the source snapshot — see OpenRouter for the billing unit
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | — |
| Writing | No measurement | — |
| Reasoning | No measurement | — |
| Document analysis | No measurement | — |
| Vision | No measurement | — |
| Image generation | No measurement | — |
| Audio | No measurement | input: audio |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Deepgram | 0 | — | — | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.