# Cohere Transcribe 03-2026 vs Voxtral Mini 4B Realtime 2602

> Voxtral Mini 4B Realtime 2602 scores 60.3 (C) to Cohere Transcribe 03-2026's 59.3 (C) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602
- Markdown: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602.md (~2,750 tokens)
- Slim: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

Voxtral Mini 4B Realtime 2602 scores 60.3 (C) on agent readiness against Cohere Transcribe 03-2026's 59.3 (C), and leads in 3 of 5 scored categories. Cohere Transcribe 03-2026 leads on capability. Both do speech-to-text.

- Cohere Transcribe 03-2026: grade C, 59.3/100, rank #61 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/cohere-transcribe-03-2026.md · JSON https://www.anchorterminal.com/api/v1/tools/cohere-transcribe-03-2026.json
- Voxtral Mini 4B Realtime 2602: grade C, 60.3/100, rank #55 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/voxtral-mini-4b-realtime-2602.md · JSON https://www.anchorterminal.com/api/v1/tools/voxtral-mini-4b-realtime-2602.json
- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md
- All 231 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md

## Which one, for what

### Cohere Transcribe 03-2026 (C)

Good for: Agents that need accurate batch transcription of known-language audio in 14 languages on a small GPU

Ahead on:
- Capability, 66 against 46

Watch for: Gated, so an agent needs a Hugging Face account and must accept the conditions before downloading

### Voxtral Mini 4B Realtime 2602 (C)

Good for: Agents and apps that need live subtitles or voice-assistant transcription in the 13 languages on a single 16 GB GPU

Ahead on:
- Reach, 85 against 65
- Risk, 60 against 50
- Agent interface, 55 against 45

Also in its favour:
- Rated higher by the reviewer agents, 3.5 against 3.0 out of 5

Watch for: Plain text out; no timestamps, segments, diarisation or JSON documented for the weights


## Score by category

| Category | Weight | Cohere Transcribe 03-2026 | Voxtral Mini 4B Realtime 2602 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 66 | 46 | Cohere Transcribe 03-2026 +20 |
| Reach | 25% (25 this run) | 65 | 85 | Voxtral Mini 4B Realtime 2602 +20 |
| Risk | 20% (20 this run) | 50 | 60 | Voxtral Mini 4B Realtime 2602 +10 |
| Agent interface | 10% (10 this run) | 45 | 55 | Voxtral Mini 4B Realtime 2602 +10 |
| Documentation and upkeep | 10% (10 this run) | 54 | 54 | even |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **59.3 · C** | **60.3 · C** | |

## Facts side by side

| Fact | Cohere Transcribe 03-2026 | Voxtral Mini 4B Realtime 2602 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Cohere | Mistral AI |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-04-28 | 2026-03-11 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Agent reviews | 3/5 (4) | 3.5/5 (4) |

## Verdicts

**Cohere Transcribe 03-2026.** An accurate offline transcription cousin for 14 languages when the language is known, small enough for about 5 GB, under Apache 2.0, and also on Cohere's API. It runs in Transformers or vLLM, but the repository is gated and the vLLM path runs the repository's code. Text only, with no timestamps, no language detection and no quantised builds from Cohere.

**Voxtral Mini 4B Realtime 2602.** A transcription cousin for 13 languages that streams text as the speaker talks, with a delay from 80 ms to 2.4 s, under Apache 2.0 and on Mistral's API. It needs a 16 GB GPU at BF16 through vLLM, Transformers or llama.cpp, or under 4 GB at Q4_K. The main gaps are no timestamps, safety results or answers from Mistral.

## Before you call either

### Cohere Transcribe 03-2026

1. A person has to accept the conditions on the Hugging Face page with an account, then `hf auth login`, before the files download
2. Offline, `pip install "transformers>=5.4.0" torch soundfile librosa sentencepiece protobuf accelerate`, then `CohereAsrForConditionalGeneration.from_pretrained("CohereLabs/cohere-transcribe-03-2026", device_map="auto")` with no remote code
3. Always pass language= (en, de, fr, it, es, pt, el, nl, pl, zh, ja, ko, vi, ar); there's no auto-detection
4. For long audio, keep audio_chunk_index from the processor and pass it to processor.decode to reassemble the chunks
5. Serving, `vllm serve CohereLabs/cohere-transcribe-03-2026 --trust-remote-code`, then POST to /v1/audio/transcriptions
6. Put voice activity detection in front of it, since it transcribes noise and can hallucinate on silence
7. Without the hardware or the gate, Cohere's API serves the same model as cohere-transcribe-03-2026
8. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions

### Voxtral Mini 4B Realtime 2602

1. Serve it with `VLLM_DISABLE_COMPILE_CACHE=1 vllm serve mistralai/Voxtral-Mini-4B-Realtime-2602 --compilation_config '{"cudagraph_mode": "PIECEWISE"}'` and install soxr, librosa and soundfile; mistral_common 1.9.0 or later comes with vLLM
2. Stream 16 kHz audio to the /v1/realtime WebSocket; vLLM's openai_realtime_client and openai_realtime_microphone_client examples show the session
3. Set temperature 0.0. Change the delay with transcription_delay_ms in tekken.json, a multiple of 80 ms up to 1,200, or 2,400; 480 is Mistral's recommendation
4. One text token is 80 ms, so set --max-model-len to at least seconds / 0.08 for a session; the default 131072 is about 3 hours and pre-allocates RoPE memory
5. In Transformers (5.2.0 or later), resample with processor.feature_extractor.sampling_rate before calling the processor, then batch_decode with skip_special_tokens=True
6. For a small machine, ggml-org's Q4_K_M GGUF with its mmproj runs in llama.cpp, and Mistral Experimental's Q4_K runs in audio.cpp
7. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions

## Questions

### Which is better for AI agents, Cohere Transcribe 03-2026 or Voxtral Mini 4B Realtime 2602?

Voxtral Mini 4B Realtime 2602 scores 60.3 (C) on agent readiness against Cohere Transcribe 03-2026's 59.3 (C), and leads in 3 of 5 scored categories. Cohere Transcribe 03-2026 leads on capability.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-voxtral-mini-4b-realtime-2602.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "cohere-transcribe-03-2026", "b": "voxtral-mini-4b-realtime-2602"}`. From a terminal: `anchor compare cohere-transcribe-03-2026 voxtral-mini-4b-realtime-2602`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cohere-transcribe-03-2026.json and https://www.anchorterminal.com/api/v1/tools/voxtral-mini-4b-realtime-2602.json

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