# Nemotron 3.5 Transcribe 30B-A4B vs Underdog Bark 3.0 (slim)

> Nemotron 3.5 Transcribe 30B-A4B scores 61 (C) to Underdog Bark 3.0's 48.2 (D) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-underdog-bark-3.md (~4,650 tokens) · this version ~930 tokens · JSON https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-underdog-bark-3.json · canonical https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-underdog-bark-3
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Nemotron 3.5 Transcribe 30B-A4B scores 61 (C) on agent readiness against Underdog Bark 3.0's 48.2 (D), and leads in every scored category. 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
- Underdog Bark 3.0: D 48.2, rank #152 of 160 open-weight models · https://www.anchorterminal.com/tools/underdog-bark-3.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 Reach, 75 against 65; Risk, 75 against 40; Agent interface, 85 against 35; Documentation and upkeep, 77 against 49.
- Underdog Bark 3.0, good for Agents on Apple silicon or small machines that need English transcripts from a very small download, can run Conway's loader, and can accept accuracy nobody independent has measured

| Category | Nemotron 3.5 Transcribe 30B-A4B | Underdog Bark 3.0 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 65 |
| Risk (20%) | 75 | 40 |
| Agent interface (10%) | 85 | 35 |
| Documentation and upkeep (10%) | 77 | 49 |

| Fact (where they differ) | Nemotron 3.5 Transcribe 30B-A4B | Underdog Bark 3.0 |
| --- | --- | --- |
| Vendor | NVIDIA | Conway Research |
| Licence | OpenMDW-1.1 | CC-BY-4.0 |
| Last release | 2026-10-29 | 2026-10-15 |
| Terms last updated | not read yet | no date given |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Agent interface, Nemotron 3.5 Transcribe 30B-A4B +50: 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.); Underdog Bark 3.0 35 (Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns.)
- Risk, Nemotron 3.5 Transcribe 30B-A4B +35: 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.); Underdog Bark 3.0 40 (File safety gets 15, no pickle anywhere in a format of Conway's own, less 10 because every documented route runs the repository's Python.)
- Documentation and upkeep, Nemotron 3.5 Transcribe 30B-A4B +28: 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…); Underdog Bark 3.0 49 (The card misses the audio length it takes and a knowledge cut-off (14).)
- Reach, Nemotron 3.5 Transcribe 30B-A4B +10: 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.); Underdog Bark 3.0 65 (Memory earns the full 30, since model.bark is 163 MB and even the FP32 the loader expands it to stays near 3 GB with the fifth added.)