Parakeet Unified EN 0.6B vs Qwen3-ASR-1.7B

Parakeet Unified EN 0.6B 79

Model card 14, Intended use, limitations (buffered streaming only, accuracy falling at 160 ms and below), architecture, parameters (600M) and the language are there. Training data 20, the card lists the training datasets by name, with hours for the four Granary subsets and about 250,000 hours in all, says how the transcripts were made, and NVIDIA publishes Granary on Hugging Face. Last change 10, the last commit to the repository, on 9 June 2026, edited the card, 154 days before this check and within 180. Responsiveness 20, All 5 discussions that aren't pull requests (8 April to 24 June 2026) have a reply from an NVIDIA member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release of the unified model. File health 10, one archive and a card that agree on the model's name, size and NeMo as the way to load it. 14 + 20 + 10 + 20 + 5 + 10 = 79.

Qwen3-ASR-1.7B 33

The card covers intended use, architecture and languages and misses limitations, a parameter figure, context length and a cut-off (8). Training data is a general description in the technical report with no cut-off (5). The last change to the model's files was the -hf template on 22 July 2026, 103 days before 2 November (10). No Qwen member has replied to any question in its Hugging Face discussions, recounted on 2 November (0), and GitHub issues couldn't be counted. It's a first release (5). Files agree with the card, but a loading report and a generation_config fix wait unanswered (5).

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.

Qwen3-ASR-1.7B 75

Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. Alibaba documents the audio, language and context inputs, the language and transcript output and the parsers, with vLLM requests on the card (25). It was trained to use context and a forced language, one clip at a time (10). Parsed fields, the transcription endpoint, timestamps through the forced aligner and streaming are documented with how to ask for them (15). A Jinja template ships in both repositories (20). Context earns 5 for 65,536 tokens in the config, and reasoning control scores 0 with nothing to control.

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.

Qwen3-ASR-1.7B 75

Memory earns 30 because Alibaba's smallest build, the -hf BF16 repository, is 4.09 GB, about 4.9 GB with the fifth added, well within 16 GB. Runtimes earn 20 for vLLM, SGLang, llama.cpp and Transformers, each running it in a released version from its own code, while Ollama and LM Studio have no library entry. Builds score 0 because Alibaba publishes BF16 only. Apache 2.0 with nothing added gives terms the full 15 and the ungated repositories give download the full 10. Hosted too scores 0, with one live provider on Hugging Face and Model Studio serving a separately named Flash model.

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.

Qwen3-ASR-1.7B 55

File safety gets 25, safetensors only and loaded by the runtimes' own code with a Jinja template. Provenance gets 15 for files in Qwen's own organisation with SHA-256 hashes. Apache 2.0 carries none of the licence deductions, so licence risk keeps 15. Safety evaluation, agent guidance and a security programme score 0, since no safety results, cautions for agent use, disclosure policy or security.txt were found.