# Ming-3.0-audio-tiny vs Nemotron 3.5 Transcribe 30B-A4B (slim)

> Nemotron 3.5 Transcribe 30B-A4B scores 61 (C) to Ming-3.0-audio-tiny's 52.1 (D) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-transcribe-30b-a4b.md (~4,600 tokens) · this version ~880 tokens · JSON https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-transcribe-30b-a4b.json · canonical https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-nemotron-3-5-transcribe-30b-a4b
- 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 Ming-3.0-audio-tiny's 52.1 (D), and leads in every scored category. Both do speech-to-text.

- Ming-3.0-audio-tiny: D 52.1, rank #140 of 160 open-weight models · https://www.anchorterminal.com/tools/ming-3-0-audio-tiny.min.md
- 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
- Ming-3.0-audio-tiny, good for Self-hosted Chinese and English transcription, audio questions and spoken replies with tool calls on one GPU with about 25 GB free
- 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 45; Risk, 75 against 50; Agent interface, 85 against 65; Documentation and upkeep, 77 against 61.

| Category | Ming-3.0-audio-tiny | Nemotron 3.5 Transcribe 30B-A4B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 45 | 75 |
| Risk (20%) | 50 | 75 |
| Agent interface (10%) | 65 | 85 |
| Documentation and upkeep (10%) | 61 | 77 |

| Fact (where they differ) | Ming-3.0-audio-tiny | Nemotron 3.5 Transcribe 30B-A4B |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | NVIDIA |
| Licence | MIT | OpenMDW-1.1 |
| Last release | 2026-10-20 | 2026-10-29 |
| Terms last updated | no document linked | not read yet |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Reach, Nemotron 3.5 Transcribe 30B-A4B +30: Ming-3.0-audio-tiny 45 (Memory 20, the only build inclusionAI publishes is BF16 at 20.78 GB, which with a fifth on top is 24.9 GB, just past the 24 GB band, so it lands in the 32 GB ba…); 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.)
- Risk, Nemotron 3.5 Transcribe 30B-A4B +25: Ming-3.0-audio-tiny 50 (File safety 15, safetensors only with no pickle weights, less 10 because every documented way to load it runs the repository's code, and 40 compiled .pyc files…); 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.)
- Agent interface, Nemotron 3.5 Transcribe 30B-A4B +20: Ming-3.0-audio-tiny 65 (Read for open weights and, as a speech model, for what it takes and returns, while this model also has a chat interface with function calls.); 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.)
- Documentation and upkeep, Nemotron 3.5 Transcribe 30B-A4B +16: Ming-3.0-audio-tiny 61 (Model card 11, it covers intended use, architecture, parameters and languages and leaves out limitations, context length and a knowledge cut-off.); 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…)