# Nemotron 3.5 Transcribe 30B-A4B vs Voxtral Mini 4B Realtime 2602 (slim)

> Voxtral Mini 4B Realtime 2602 scores 62 (B) to Nemotron 3.5 Transcribe 30B-A4B's 61 (C) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

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Voxtral Mini 4B Realtime 2602 scores 62 (B) on agent readiness against Nemotron 3.5 Transcribe 30B-A4B's 61 (C), and leads in 1 of 4 scored categories. Nemotron 3.5 Transcribe 30B-A4B leads on risk, agent interface and documentation and upkeep. Both do speech-to-text.

- Nemotron 3.5 Transcribe 30B-A4B: C 61, rank #79 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b.min.md
- Voxtral Mini 4B Realtime 2602: B 62, rank #32 of 160 open-weight models · https://www.anchorterminal.com/tools/voxtral-mini-4b-realtime-2602.min.md
- Nemotron 3.5 Transcribe 30B-A4B, good for Teams that need accurate multilingual transcripts of long recordings with speakers and timings, and have a 32 GB GPU or better Ahead on Risk, 75 against 60; Agent interface, 85 against 55; Documentation and upkeep, 77 against 59.
- Voxtral Mini 4B Realtime 2602, 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, 90 against 75.

| Category | Nemotron 3.5 Transcribe 30B-A4B | Voxtral Mini 4B Realtime 2602 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 90 |
| Risk (20%) | 75 | 60 |
| Agent interface (10%) | 85 | 55 |
| Documentation and upkeep (10%) | 77 | 59 |

| Fact (where they differ) | Nemotron 3.5 Transcribe 30B-A4B | Voxtral Mini 4B Realtime 2602 |
| --- | --- | --- |
| Vendor | NVIDIA | Mistral AI |
| Licence | OpenMDW-1.1 | Apache-2.0 |
| Last release | 2026-10-29 | 2026-03-11 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 3.5/5 (4) |

Why the edge:
- Agent interface, Nemotron 3.5 Transcribe 30B-A4B +30: Nemotron 3.5 Transcribe 30B-A4B 85 (Chat template 20, chat_template.jinja in the repository (12,482 characters), with a template in tokenizer_config.json too.); Voxtral Mini 4B Realtime 2602 55 (Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns.)
- Documentation and upkeep, Nemotron 3.5 Transcribe 30B-A4B +18: Nemotron 3.5 Transcribe 30B-A4B 77 (Model card 17, Intended use, limitations (the explainability subcard's technical limitations), the architecture, the parameters, the context and the languages a…); Voxtral Mini 4B Realtime 2602 59 (The card covers intended use, architecture, parameters, context and languages, without limitations or a cut-off (14).)
- Reach, Voxtral Mini 4B Realtime 2602 +15: Nemotron 3.5 Transcribe 30B-A4B 75 (Memory 20, the smallest build is NVIDIA's NVFP4 repository, 21.56 GB, and 21.56 GB × 1.2 = 25.9 GB, within 32 GB.); Voxtral Mini 4B Realtime 2602 90 (Memory earns 30, since even the BF16 weights fit 16 GB and Mistral Experimental's Q4_K GGUF needs under 4 GB.)
- Risk, Nemotron 3.5 Transcribe 30B-A4B +15: Nemotron 3.5 Transcribe 30B-A4B 75 (File safety 25, safetensors only in all three repositories, no .bin, .pt or .pth files and no Python.); Voxtral Mini 4B Realtime 2602 60 (File safety gets the full 25, safetensors only and loaded by the runtimes' own code.)