Summary
The ASR NIM container nvcr.io/nim/nvidia/parakeet-1-1b-rnnt-multilingual:latest (version 1.5.0, Riva Speech 26.02) has no profiles with diarizer=disabled despite the official documentation listing them. All 60 profiles in the manifest force diarizer=sortformer. The sortformer TensorRT engine fails to deserialize on Blackwell GPUs (RTX 5080, RTX 5090, compute capability 12.0), making the container unusable on Blackwell hardware.
Environment
- Container:
nvcr.io/nim/nvidia/parakeet-1-1b-rnnt-multilingual:latest(NIM 1.5.0, Riva Speech 2.25.0, container version 26.02) - GPUs tested: RTX 5090 (sm_120), RTX 5080 (sm_120), RTX 5060 Ti (sm_120)
- Driver: 570.x
- OS: Ubuntu 24.04
- Docker: with nvidia-container-toolkit
Bug 1: Missing diarizer=disabled profiles
The official support matrix documents these profiles for Parakeet 1.1b RNNT Multilingual:
| NIM_TAGS_SELECTOR | GPU (GB) |
|---|---|
mode=str,diarizer=disabled |
9.77 |
mode=ofl,diarizer=disabled |
11.41 |
mode=str-thr,diarizer=disabled |
10.69 |
mode=all,diarizer=disabled |
28.64 |
However, when inspecting the actual container manifest (/opt/nim/etc/default/model_manifest.yaml), zero profiles have diarizer=disabled. Every single profile (60 total) has diarizer=sortformer. This includes both prebuilt profiles (for A100, H100, L40S, DGX Spark) and RMIR profiles.
Using NIM_TAGS_SELECTOR="mode=str,diarizer=disabled" results in:
NIMProfileIDNotFound: Could not match a profile in manifest
Comparison with version 1.4.0
Version 1.4.0 does include diarizer=disabled RMIR profiles and works correctly on Blackwell GPUs:
Matched profile: tags: {'diarizer': 'disabled', 'mode': 'str', 'model_type': 'rmir', 'name': 'parakeet-1-1b-rnnt-multilingual', 'vad': 'default'}
Bug 2: Sortformer engine fails to deserialize on Blackwell
When using NIM_TAGS_SELECTOR="mode=str" (without diarizer filter), the container matches an RMIR profile with diarizer=sortformer and proceeds to build TensorRT engines. The main ASR encoder builds successfully, but the sortformer diarizer engine fails to load:
[!] Could not deserialize engine.
During the sortformer engine build, there are also OOM warnings:
[TRT] [E] [virtualMemoryBuffer.cpp::resizePhysical::154] Error Code 2: OutOfMemory (Requested size was 5851054080 bytes.)
[TRT] [W] UNSUPPORTED_STATE: Skipping tactic 0 due to insufficient memory
This happens on an RTX 5080 (16GB) and RTX 5090 (32GB), so the OOM on the 5090 is suspicious — 5.85GB should fit in 32GB.
Bug 3: Versions 1.6.0, 1.7.0, and 1.8.0 documented but do not exist
The release notes document three versions that do not exist on NGC:
- 1.8.0: “Blackwell GPU support added for Parakeet 1.1b RNNT Multilingual”
- 1.7.0: “Sortformer diarizer support for Parakeet 1.1b RNNT Multilingual”
- 1.6.0: “Silero VAD and Sortformer diarizer support across multiple models”
We queried the NGC container registry API directly to obtain the complete list of published tags:
GET https://nvcr.io/v2/nim/nvidia/parakeet-1-1b-rnnt-multilingual/tags/list
Response:
{"name":"nim/nvidia/parakeet-1-1b-rnnt-multilingual","tags":["1.0.0","1.0","1.1.0","1.1","1.2.0","1.2","1.3.0","1.3","1.4.0","1.4","1.5.0","1.5","1","latest",...]}
Only versions 1.0 through 1.5 exist. There is no 1.6.0, 1.7.0, or 1.8.0 — not even for Enterprise accounts. The latest tag points to 1.5.0 (created March 2, 2026).
The documentation describes features for three unreleased versions, including the Blackwell support that users are waiting for. This creates significant confusion, as users read the release notes, see “Blackwell GPU support added in 1.8.0”, and expect to find a working container.
Additionally, the Speech NIM 26.02.0 support matrix states that Parakeet RNNT Multilingual “is supported on Blackwell and DGX Spark platform” — but the only published container (1.5.0) fails on Blackwell as described above.
Expected Behavior
- Container
latestshould includediarizer=disabledprofiles as documented - Sortformer TensorRT engines should build and load correctly on Blackwell (sm_120) GPUs
- If 1.8.0 is released, the container tag should be available on NGC
Workaround
Using version 1.4.0 which has diarizer=disabled RMIR profiles that compile and run correctly on Blackwell GPUs:
docker run -d --name parakeet-asr \
--runtime=nvidia --gpus '"device=0"' --shm-size=8GB \
-e NGC_API_KEY -e NIM_HTTP_API_PORT=9000 -e NIM_GRPC_API_PORT=50051 \
-e NIM_TAGS_SELECTOR="mode=str" \
-v ~/.cache/nim:/opt/nim/.cache \
-p 9000:9000 -p 50051:50051 \
nvcr.io/nim/nvidia/parakeet-1-1b-rnnt-multilingual:1.4.0
Steps to Reproduce
- Pull the latest container:
docker pull nvcr.io/nim/nvidia/parakeet-1-1b-rnnt-multilingual:latest - Run on any Blackwell GPU with
NIM_TAGS_SELECTOR="mode=str,diarizer=disabled"→ profile not found - Run with
NIM_TAGS_SELECTOR="mode=str"→ matches sortformer RMIR, builds engines, fails with “Could not deserialize engine”