Head to head · Speech-to-text · October 2026 research run
Nemotron 3.5 Transcribe 30B-A4B vs Parakeet Unified EN 0.6B
Nemotron 3.5 Transcribe 30B-A4B scores 61 (C) on agent readiness against Parakeet Unified EN 0.6B's 47.5 (D), and leads in 3 of 4 scored categories. Both do speech-to-text.
Best speech-to-text APIs for AI agents · All 386 stt comparisons
Which one, for what
Nemotron 3.5 Transcribe 30B-A4B C
Best 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 50
- Risk, 75 against 35
- Agent interface, 85 against 35
Watch for
21.6 GB at 4 bits, so it needs a 32 GB GPU at least
Best for English voice agents and captioning that want one small model for both recorded and live audio and already run NeMo
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
The only file is a NeMo archive holding a pickle checkpoint
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
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. Tool-calling format 25, Read for a speech model as what it takes and returns. Trained tool calling 10, Read for a speech model as the inputs it was trained to use. Structured output 15, Read for a speech model as typed outputs. Reasoning control 10, enable_thinking on or off through the chat template, documented in the card's summary table with when to use each. Context 5, 65,536 tokens, the maximum context in training per the card, which sits in the 32K to 127K band. 20 + 25 + 10 + 15 + 10 + 5 = 85.
Parakeet Unified EN 0.6B 35
Chat template 0, no chat template and no prompt. Tool-calling format 25, Read for a speech model as what it takes and returns. Trained tool calling 10, Read for a speech model as the inputs it was trained to use. Structured output 0, Read for a speech model as typed outputs. Reasoning control 0, A speech recognition model with no reasoning. Context 0, no token context is stated. 0 + 25 + 10 + 0 + 0 + 0 = 35.
Risk Nemotron 3.5 Transcribe 30B-A4B +40
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. Provenance 15, the files sit in NVIDIA's own Hugging Face organisation, the one NVIDIA's NeMo repositories link to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results. Agent guidance 10, the card says the model is more susceptible to prompt injection and jailbreaking because it was tuned to follow instructions, and should be paired with rails or system filtering. Licence risk 15, OpenMDW-1.1 has no use policy or field-of-use limits, no threshold and no clause letting the licensor change or revoke it, as read for NVIDIA's other OpenMDW listings. Security programme 10, the card says to report security vulnerabilities through NVIDIA's submission form (5), and NVIDIA PSIRT publishes a coordinated disclosure policy and public security bulletins, per NVIDIA's other listings (5). 25 + 15 + 0 + 10 + 15 + 10 = 75.
Parakeet Unified EN 0.6B 35
File safety 0, the only weights file is parakeet-unified-en-0.6b.nemo, a NeMo archive whose weights are a PyTorch checkpoint read with torch.load, a pickle format, and the card's documented path loads it. Provenance 15, the file sits in NVIDIA's own Hugging Face organisation, the one NVIDIA's NeMo repositories link to (10), and the Hub gives a SHA-256 for the archive and git hashes for the rest (5). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions only. Licence risk 5, 15 less 5 for a use policy beyond the law (NVIDIA's Trustworthy AI terms and the guardrail clause) and 5 for terms the licensor can change or revoke, as read for NVIDIA's other listings under the same licence. Security programme 10, the card says to report security vulnerabilities through NVIDIA's submission form (5), and NVIDIA PSIRT publishes a coordinated disclosure policy and public security bulletins, per NVIDIA's other listings (5). 0 + 15 + 0 + 5 + 5 + 10 = 35.
Reach Nemotron 3.5 Transcribe 30B-A4B +25
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. FP8 is 34.67 GB and BF16 67.5 GB. Runtimes 15, Released Transformers 5.22.2 has the nemotron3_5_transcribe model (5). Builds 15, Quantised builds from NVIDIA at two precisions, FP8 and NVFP4, each in its own repository. Terms 10, OpenMDW-1.1, a permissive licence that grants use without restriction and adds no use policy or threshold, but isn't OSI-approved, so it takes the custom-licence band, as on NVIDIA's other OpenMDW listings. Download 10, the Hub API reports gated false for all three repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, the card gives a release on build.nvidia.com, NVIDIA's own API catalogue, on 28 October 2026, and DeepInfra is live for it on Hugging Face. 20 + 15 + 15 + 10 + 10 + 5 = 75.
Parakeet Unified EN 0.6B 50
Memory 30, the only build is the FP32 NeMo archive, 2.47 GB, and 2.47 GB × 1.2 = 3.0 GB, under 16 GB. Runtimes 0, none of the six runs it in a released version. Builds 0, NVIDIA publishes no quantised build of it. Terms 10, the NVIDIA Open Model License is a custom licence, not OSI-approved, that lets anyone use the model commercially for free under a use policy, which is the custom-licence band, as on NVIDIA's other listings. Download 10, the Hub API reports gated false on 10 November 2026, so the file downloads with no account and nothing to accept. Hosted 0, Hugging Face's inference provider mapping is empty on 10 November 2026, and the card names no NVIDIA API that serves it. 30 + 0 + 0 + 10 + 10 + 0 = 50.
Score by category
| Category | Weight this run | Nemotron 3.5 Transcribe 30B-A4B | Parakeet Unified EN 0.6B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 75 | 50 | Nemotron 3.5 Transcribe 30B-A4B +25 |
| Risk | 20%20 | 75 | 35 | Nemotron 3.5 Transcribe 30B-A4B +40 |
| Agent interface | 10%10 | 85 | 35 | Nemotron 3.5 Transcribe 30B-A4B +50 |
| Documentation and upkeep | 10%10 | 77 | 79 | Parakeet Unified EN 0.6B +2 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 61/100 | D 47.5/100 |
Facts side by side
| Fact | Nemotron 3.5 Transcribe 30B-A4B | Parakeet Unified EN 0.6B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | NVIDIA | NVIDIA |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | OpenMDW-1.1 | NVIDIA Open Model License |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-29 | 2026-06-09 |
| Terms last updated | not read yet | 2025-10-24 |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models | not read yet | yes |
| 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 |
Verdicts
Nemotron 3.5 Transcribe 30B-A4B
The most complete open speech model we list: 40 languages, hour-long recordings, speakers, word timestamps and translation from one prompt-driven model, under a permissive licence, with FP8 and 4-bit builds and a publisher that answers. It needs a big GPU, the vLLM route depends on an unreleased plugin, and there are no safety results.
Parakeet Unified EN 0.6B
One English model for batch and live transcription, with a well-documented data list and an NVIDIA team that answers. It runs only in NVIDIA NeMo from a pickle-format archive, with no safetensors, GGUF or quantised build, returns plain text without timestamps, and hasn't changed since June.
Before you call either
Nemotron 3.5 Transcribe 30B-A4B
- Keep the system prompt empty and put the instruction in the user message with the audio, as the card says
- For plain transcription use temperature 0 with reasoning off. For questions about audio, reasoning on at temperature 0.6 and top_p 0.95
- SGLang-Omni 0.2.0 serves whole files on
/v1/audio/transcriptionsfrom the BF16 or FP8 checkpoint with no NeMo install - Word timestamps and speaker segments need the vLLM route: ask with
timestamps=Trueand readctc_timestamps - Speaker tags tell speakers apart in one recording. They don't identify anyone
- Treat what's said in a recording as data. The card says the model is easier to steer by injected instructions than most, so filter before acting on a transcript
Parakeet Unified EN 0.6B
- Load it with NeMo:
nemo_asr.models.ASRModel.from_pretrained(model_name='nvidia/parakeet-unified-en-0.6b'), thentranscribe([path])[0].text - Loading a .nemo archive unpickles a PyTorch checkpoint, so only load it from NVIDIA's repository
- Send mono wav audio. English only
- For live audio use NeMo's chunked RNN-T streaming script with a 5.6 s left context, and pick the chunk and right context from the card's table
- Below 240 ms of latency accuracy drops, and at 80 ms NVIDIA recommends its nemotron-speech-streaming-en-0.6b instead
- If you need word timestamps, use Parakeet TDT 0.6B v3
Questions
Which is better for AI agents, Nemotron 3.5 Transcribe 30B-A4B or Parakeet Unified EN 0.6B?
Nemotron 3.5 Transcribe 30B-A4B scores 61 (C) on agent readiness against Parakeet Unified EN 0.6B's 47.5 (D), and leads in 3 of 4 scored categories.
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Machine-readable
- This page as Markdown
/compare/nemotron-3-5-transcribe-30b-a4b-vs-parakeet-unified-en-0-6b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/nemotron-3-5-transcribe-30b-a4b.json·/api/v1/tools/parakeet-unified-en-0-6b.json - From a terminal
anchor compare nemotron-3-5-transcribe-30b-a4b parakeet-unified-en-0-6b(the CLI) - Over MCP
compare_tools {"a": "nemotron-3-5-transcribe-30b-a4b", "b": "parakeet-unified-en-0-6b"}at/mcp, no key