> ## Documentation Index
> Fetch the complete documentation index at: https://polargrid.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Cohere Transcribe (03-2026)
> Multilingual high-accuracy speech-to-text on PolarGrid edge nodes
Cohere Transcribe (`cohere-transcribe-03-2026`) is a 2-billion-parameter multilingual speech-to-text model served on PolarGrid edge nodes via Triton's `python` backend. The voice pod runs `transformers >= 5.4` to support this model — see [`backend/edge-production-setup/CLAUDE.md`](https://github.com/PolarGrid-AI/polargrid-monorepo/blob/main/backend/edge-production-setup/CLAUDE.md) for the pod split rationale.
* **HF repo:** [`CohereLabs/cohere-transcribe-03-2026`](https://huggingface.co/CohereLabs/cohere-transcribe-03-2026)
* **Modality:** Speech-to-Text (streaming + sync)
* **Backend:** Triton `python` (voice pod)
* **Model ID:** `cohere-transcribe-03-2026` (use the full ID; the short alias `cohere-transcribe` is not routable on the gateway)
- **Available regions:** all regions except `dfw-02` — see [Model availability](/guides/model-availability)
## Headline benchmark
`POST /v1/audio/transcriptions?stream=true` is the live surface. The server emits a `text/event-stream` of `transcript.text.delta` events as the cohere handler's internal decode loop completes each window, then closes with a single `transcript.text.done` event. Consumers can render the rolling transcript immediately instead of waiting for the final result.
| Measurement | p50 | p95 |
| --------------------------------------------------- | --------- | ------- |
| **TTFT (response headers → first non-empty delta)** | **44 ms** | 62 ms |
| Time to `done` event (response headers → done) | 560 ms | 856 ms |
| Interim work (first delta → done) | 517 ms | 816 ms |
| Delta events per request | 4 | 7 (max) |
| Partial deltas (text != final) | 4 | — |
| e2e total (POST → `[DONE]`) | 2510 ms | 3523 ms |
| **RTF (e2e ÷ audio duration)** | **0.42** | 0.53 |
| well\_formed | 100 / 100 | — |
*Bench: 100 streaming transcription runs against `https://api.yvr-02.edge.polargrid.ai`, captured 2026-05-28 from a Vancouver-area laptop. Inputs were 5 short utterances (4.2 – 7.7 s, 24 kHz mono WAV, \~200–350 KB each) pre-synthesized via `tada-3b-ml` on the same node — see [`bench/cohere-transcribe-03-2026/synthesize_inputs.py`](https://github.com/PolarGrid-AI/polargrid-monorepo/tree/main/backend/edge-production-setup/bench/cohere-transcribe-03-2026). Raw runs: [`benchmarks/yvr-02-2026-05-28/cohere-transcribe-03-2026/`](https://github.com/PolarGrid-AI/polargrid-monorepo/blob/main/benchmarks/yvr-02-2026-05-28/cohere-transcribe-03-2026/cohere-transcribe-03-2026_streaming_bench.json).*
> **Delta cadence is chunk-driven.** 4.2 – 5.9 s clips emit 4 deltas, 7.2 – 7.7 s clips emit 7. Each delta carries a non-overlapping span of the transcript; concatenating them reconstructs the final string. The first delta arriving at 44 ms after response headers is the meaningful TTFT for live-captioning pipelines. The gateway does not emit `X-Pg-Inference-Ms` on the stream surface yet, so server-only inference cannot be quoted client-side for streaming today.
## How this compares
| Provider | Streaming first-partial p50 | Sync RTF | Notes | Source |
| ------------------------------------------------------ | -------------------------------------------- | --------------------- | ------------------------------------------------ | ------------------------------------------------------------------------------------- |
| **PolarGrid `cohere-transcribe-03-2026` on Blackwell** | **44 ms** after response headers | **0.041** server-only | 14 languages, sync + streaming surfaces | this card |
| Deepgram Nova-3 | sub-300 ms over WebSocket from end-of-speech | n/a | WebSocket protocol streams audio in continuously | [artificialanalysis.ai](https://artificialanalysis.ai/speech-to-text/models/deepgram) |
| AssemblyAI Universal-3 | n/a | \~0.008 to 0.05 batch | Batch transcription tier | [assemblyai.com](https://www.assemblyai.com/benchmarks) |
PolarGrid's 44 ms streaming TTFT is gated by the multipart audio upload arriving first; total client wall-clock to first partial is closer to 1970 ms p50 (TTFB 1926 ms + first-delta 44 ms) on a 300 KB WAV. Deepgram Nova-3 measures streaming TTFT from end-of-speech because the WebSocket protocol streams audio in continuously, which removes the upload component entirely. For mic-to-screen pipelines that need sub-300 ms first-partial from end-of-speech, an audio-streaming-in protocol (WebSocket or chunked-upload) is the missing piece on PolarGrid today. For batch-upload workloads PolarGrid's server-only RTF of 0.041 is in the same tier as AssemblyAI Universal-3 batch.
## Quickstart
Edge endpoints accept your raw `pg_*` API key as a bearer token — no token exchange. See [Authentication](/authentication).
```bash cURL theme={null}
curl -X POST "https://api.yvr-02.edge.polargrid.ai/v1/audio/transcriptions?sync=true&model=cohere-transcribe-03-2026" \
-H "Authorization: Bearer $POLARGRID_API_KEY" \
-F "file=@input.wav"
```
```typescript JavaScript theme={null}
import { PolarGrid } from "@polargrid/polargrid-sdk";
import fs from "node:fs";
const client = await PolarGrid.create({ apiKey: process.env.POLARGRID_API_KEY });
const result = await client.audioTranscriptions({
model: "cohere-transcribe-03-2026",
file: fs.createReadStream("input.wav"),
// Default mode is async (returns job_id). Pass sync to block on the result.
sync: true,
});
console.log(result.text);
```
```python Python theme={null}
from polargrid import PolarGrid
client = await PolarGrid.create(api_key="pg_...")
with open("input.wav", "rb") as f:
result = await client.audio_transcriptions({
"model": "cohere-transcribe-03-2026",
"file": f,
"sync": True,
})
print(result["text"])
```
## Endpoint modes
`POST /v1/audio/transcriptions` has three modes selected by query params (not multipart fields):
| Mode | Query | Response | Use when |
| ------------------- | -------------- | ----------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| **Streaming** | `?stream=true` | `text/event-stream` of delta + done events | Live captioning; sub-utterance partial transcripts as the model decodes. **This is what the headline bench above measures.** |
| **Sync** | `?sync=true` | `200` with the formatted transcript directly | Voice-agent path that needs the answer in one round trip. |
| **Async (default)** | *none* | `202` with `{job_id, poll_url}`; poll via `GET ?job_id=...` | Background batch transcription; no caller blocking. |
`stream` and `sync` are mutually exclusive — passing both returns `400`. Streaming requires `response_format` in `{json, text}`.
### Sync benchmark (`?sync=true`)
The blocking surface holds the connection open until inference completes, then ships the whole JSON response. Client-side TTFB ≈ total wall-clock, and the meaningful split is **server inference time** vs **network leg** (which for STT is dominated by the audio upload). Raw runs: [`benchmarks/yvr-02-2026-05-27/cohere-transcribe-03-2026/`](https://github.com/PolarGrid-AI/polargrid-monorepo/blob/main/benchmarks/yvr-02-2026-05-27/cohere-transcribe-03-2026/cohere-transcribe-03-2026_bench.json).
| Measurement | p50 | p95 |
| --------------------------------------- | ---------- | ------- |
| End-to-end TTFB (with network + upload) | 1068 ms | 1535 ms |
| **Server-only inference** | **238 ms** | 305 ms |
| *Network leg (e2e − server)* | *831 ms* | — |
| Body transfer (JSON response) | 0.7 ms | 1.6 ms |
| RTF (server inference ÷ audio duration) | 0.041 | 0.056 |
Server-only timing comes from the `X-Pg-Inference-Ms` response header (PR #507), available on the sync surface.
> **The network leg is upload-dominated.** Each request ships a multi-second WAV file before inference can begin, so the 831 ms p50 network figure is largely the upload time of a \~300 KB body — not POP-to-client RTT. For shorter clips (sub-2 s) the network leg shrinks proportionally. Quote the **server-only RTF** when comparing inference throughput against centralized providers.
## Capabilities
| Field | Value | |
| ------------------ | -------------------------------------------------------------------------------------------------------------------------- | ------- |
| Endpoint | `POST /v1/audio/transcriptions` | |
| Multipart field | `file` (required) | |
| Query params | `model`, `language`, `prompt`, `temperature`, `response_format`, `punctuation`, `stream`, `sync` | |
| `response_format` | `json` (default), `text`, `srt`, `vtt`, `verbose_json` | |
| Languages | English, French, German, Italian, Spanish, Portuguese, Greek, Dutch, Polish, Chinese, Japanese, Korean, Vietnamese, Arabic | |
| Punctuation toggle | Yes — pass \`punctuation=true | false\` |
| Max batch size | 1 | |
| Backend pod | `inference-backend-triton-voice` | |
## Response timing headers
PR #507 added two response headers that bench harnesses and observability tooling can read to get a server-only inference time without inferring it from the body:
| Header | Value |
| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `X-Pg-Inference-Ms` | Integer milliseconds — wall-clock around the `transcribe()` call inside the gateway's `_handle_sync` (i.e., excludes the audio upload + response transfer). |
| `Server-Timing` | Standard-shape `inference;dur=` entry carrying the same number. |
These let callers compute the network leg as `(client wall-clock) − (X-Pg-Inference-Ms)`, the same e2e-vs-server split available for LLM via `pg_metadata`.
## Model identifier
Call this model with the full id `cohere-transcribe-03-2026` at `/v1/audio/transcriptions`. The short alias `cohere-transcribe` is **not routable** on the gateway (returns 404). The HuggingFace repo id `CohereLabs/cohere-transcribe-03-2026` is accepted at `/v1/models/load` for hot-loading purposes but does not resolve at inference time.
## Notes
* License: [Apache 2.0](https://huggingface.co/CohereLabs/cohere-transcribe-03-2026/blob/main/LICENSE) (no auth required to pull weights).
* Voice pod isolation: this model needs `transformers >= 5.4`, which conflicts with hume-tada's `< 5` pin and the LLM pod's vLLM 0.17.x. That's why PolarGrid splits voice/LLM/TADA into three Triton pods — see [`backend/edge-production-setup/CLAUDE.md`](https://github.com/PolarGrid-AI/polargrid-monorepo/blob/main/backend/edge-production-setup/CLAUDE.md).
* For lower full-utterance latency, [`whisper-large-v3-turbo`](/models/whisper-large-v3-turbo) is the alternative — Cohere's edge is multilingual coverage + accuracy on accented speech.
## See also
* [Speech-to-Text API](/api-reference/speech-to-text) — endpoint reference, formats, streaming contract
* [Voice AI guide](/guides/voice) — building voice agents on PolarGrid
* [Authentication](/authentication) — using your `pg_*` API key
* [`/v1/models`](/api-reference/models) — list all available models