Comparison
LLaMA-Omni vs whisper
Verdict
Pick LLaMA-Omni if lLaMA-Omni is a specialized multimodal large language model tailored for enhancing speech interaction capabilities through advanced integration of speech-to-speech and speech-to-text functionalities; pick whisper if whisper is a speech recognition model that uses large-scale weak supervision to transcribe audio to text with high accuracy.
Markdown twin · LLaMA-Omni alternatives · whisper alternatives
GraphCanon updated Sep 20, 2026
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Trust & integrity
| Signal | LLaMA-Omni | whisper |
|---|---|---|
| Maintenance | Dormant (489d since push) As of Sep 20, 2026 · github_public_v1 | Active (17d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No published findings from this source as of 2026-09-18 As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- LLaMA-Omni
- End-to-end speech interaction model based on Llama-3.1-8B-Instruct
- whisper
- Robust Speech Recognition via Large-Scale Weak Supervision
Stars
- LLaMA-Omni
- 3.1k
- whisper
- 109k
Forks
- LLaMA-Omni
- 225
- whisper
- 13k
Open issues
- LLaMA-Omni
- 52
- whisper
- 149
Language
- LLaMA-Omni
- Python
- whisper
- Python
Adopt for
- LLaMA-Omni
- LLaMA-Omni is a specialized multimodal large language model tailored for enhancing speech interaction capabilities through advanced integration of speech-to-speech and speech-to-text functionalities.
- whisper
- Whisper is a speech recognition model that uses large-scale weak supervision to transcribe audio to text with high accuracy.
Persona
- LLaMA-Omni
- -
- whisper
- -
Runtime
- LLaMA-Omni
- -
- whisper
- -
License
- LLaMA-Omni
- Apache-2.0
- whisper
- Whisper is released under the MIT License, allowing for broad use and modification.
Last pushed
- LLaMA-Omni
- May 19, 2025
- whisper
- Aug 31, 2026
Categories
- LLaMA-Omni
- Speech & Audio
- whisper
- Speech & Audio
Trust and health
Maintenance
- LLaMA-Omni
- Dormant (18%)
- whisper
- Active (82%)
Days since push
- LLaMA-Omni
- 489d
- whisper
- 17d
Open issues (now)
- LLaMA-Omni
- 52
- whisper
- 149
Stars delta
- LLaMA-Omni
- +2 (30d)
- whisper
- +2.6k (30d)
Open issues delta
- LLaMA-Omni
- 0 (30d)
- whisper
- +14 (30d)
OSV dependency advisories
- LLaMA-Omni
- No lockfile (source not queried)
- whisper
- No published findings from this source as of 2026-09-18
Full report
- LLaMA-Omni
- Trust report
- whisper
- Trust report
Typed relationship
LLaMA-Omni whisperBoth LLaMA-Omni and Whisper deal with speech processing, but they serve different purposes. Whisper focuses on robust speech recognition, while LLaMA-Omni is about generating both text and speech responses from speech inputs.
Choose LLaMA-Omni if…
- License: LLaMA-Omni is Apache-2.0, whisper is MIT.
- Both LLaMA-Omni and Whisper deal with speech processing, but they serve different purposes. Whisper focuses on robust speech recognition, while LLaMA-Omni is about generating both text and speech responses from speech inputs.
- Tags unique to LLaMA-Omni: large-language-models, multimodal-large-language-models, speech-interaction, speech-language-model.
- - When targeting low-latency, high-quality end-to-end speech interactions that need to be performed in an academic research environment.
When NOT to use LLaMA-Omni
- - Avoid LLaMA-Omni if your project requires commercial deployment since its usage rights are strictly non-commercial.
- - If real-time interaction constraints are less critical than achieving high-quality speech output, another tool with more flexibility regarding latency and deployment options may be preferable.
Choose whisper if…
- License: whisper is MIT, LLaMA-Omni is Apache-2.0.
- Requirements: Whisper requires Python and specific dependencies for running the model..
- Both LLaMA-Omni and Whisper deal with speech processing, but they serve different purposes. Whisper focuses on robust speech recognition, while LLaMA-Omni is about generating both text and speech responses from speech inputs.
- Tags unique to whisper: audio transcription, mit license, python, speech recognition.
- When you need a tool that leverages large-scale weak supervision for robust speech recognition.
When NOT to use whisper
- If your project requires real-time speech recognition, as Whisper may not be optimized for low-latency applications.
- When you need a tool that supports a wide range of languages beyond those covered by Whisper's model.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (ictnlp/LLaMA-Omni) · observed Sep 20, 2026
- GitHub forks (ictnlp/LLaMA-Omni) · observed Sep 20, 2026
- Last push (ictnlp/LLaMA-Omni) · observed May 19, 2025
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 10, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (openai/whisper) · observed Sep 20, 2026
- GitHub forks (openai/whisper) · observed Sep 20, 2026
- Last push (openai/whisper) · observed Aug 31, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: LLaMA-Omni 3.1k · whisper 109k (synced Sep 20, 2026).
Common questions
- What is the difference between LLaMA-Omni and whisper?
- LLaMA-Omni: End-to-end speech interaction model based on Llama-3.1-8B-Instruct. whisper: Robust Speech Recognition via Large-Scale Weak Supervision. See the comparison table for live GitHub stats and shared categories.
- When should I choose LLaMA-Omni over whisper?
- Choose LLaMA-Omni over whisper when License: LLaMA-Omni is Apache-2.0, whisper is MIT; Both LLaMA-Omni and Whisper deal with speech processing, but they serve different purposes. Whisper focuses on robust speech recognition, while LLaMA-Omni is about generating both text and speech responses from speech inputs; Tags unique to LLaMA-Omni: large-language-models, multimodal-large-language-models, speech-interaction, speech-language-model; - When targeting low-latency, high-quality end-to-end speech interactions that need to be performed in an academic research environment.
- When should I choose whisper over LLaMA-Omni?
- Choose whisper over LLaMA-Omni when License: whisper is MIT, LLaMA-Omni is Apache-2.0; Requirements: Whisper requires Python and specific dependencies for running the model.; Both LLaMA-Omni and Whisper deal with speech processing, but they serve different purposes. Whisper focuses on robust speech recognition, while LLaMA-Omni is about generating both text and speech responses from speech inputs; Tags unique to whisper: audio transcription, mit license, python, speech recognition; When you need a tool that leverages large-scale weak supervision for robust speech recognition.
- When should I avoid LLaMA-Omni?
- - Avoid LLaMA-Omni if your project requires commercial deployment since its usage rights are strictly non-commercial. - If real-time interaction constraints are less critical than achieving high-quality speech output, another tool with more flexibility regarding latency and deployment options may be preferable.
- When should I avoid whisper?
- If your project requires real-time speech recognition, as Whisper may not be optimized for low-latency applications. When you need a tool that supports a wide range of languages beyond those covered by Whisper's model.
- Is LLaMA-Omni or whisper more popular on GitHub?
- whisper has more GitHub stars (109,313 vs 3,148). Stars measure visibility, not whether either tool fits your constraints.
- Are LLaMA-Omni and whisper open source?
- Yes - both are open-source projects on GitHub (LLaMA-Omni: Apache-2.0, whisper: MIT).
- Where can I find alternatives to LLaMA-Omni or whisper?
- GraphCanon lists graph-backed alternatives at LLaMA-Omni alternatives and whisper alternatives (LLaMA-Omni markdown twin, whisper markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, LLaMA-Omni or whisper?
- LLaMA-Omni: Dormant. whisper: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for LLaMA-Omni and whisper?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLaMA-Omni trust report; whisper trust report.