Comparison
FasterTransformer vs faster-whisper
Verdict
Pick FasterTransformer if highly optimized transformer encoder and decoder for inferencing, supporting BERT and GPT on various frameworks like TensorFlow, PyTorch; pick faster-whisper if a package for faster speech-to-text transcription based on the Whisper model, using CTranslate2.
Markdown twin · FasterTransformer alternatives · faster-whisper alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | FasterTransformer | faster-whisper |
|---|---|---|
| Maintenance | Dormant (862d since push) As of 2w · github_public_v1 | Slowing (255d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No published findings from this source as of 2026-07-11 As of 1mo · 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
- FasterTransformer
- Transformer related optimization including BERT and GPT
- faster-whisper
- Faster Whisper transcription with CTranslate2
Stars
- FasterTransformer
- 6.4k
- faster-whisper
- 25k
Forks
- FasterTransformer
- 935
- faster-whisper
- 2.0k
Open issues
- FasterTransformer
- 289
- faster-whisper
- 315
Language
- FasterTransformer
- C++
- faster-whisper
- Python
Adopt for
- FasterTransformer
- Highly optimized transformer encoder and decoder for inferencing, supporting BERT and GPT on various frameworks like TensorFlow, PyTorch.
- faster-whisper
- A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2.
Persona
- FasterTransformer
- -
- faster-whisper
- -
Runtime
- FasterTransformer
- -
- faster-whisper
- -
License
- FasterTransformer
- Apache-2.0
- faster-whisper
- MIT
Last pushed
- FasterTransformer
- Mar 27, 2024
- faster-whisper
- Nov 19, 2025
Categories
- FasterTransformer
- Inference & Serving
- faster-whisper
- Inference & Serving, Speech & Audio
Trust and health
Maintenance
- FasterTransformer
- Dormant (18%)
- faster-whisper
- Slowing (36%)
Days since push
- FasterTransformer
- 862d
- faster-whisper
- 255d
Open issues (now)
- FasterTransformer
- 289
- faster-whisper
- 315
OSV dependency advisories
- FasterTransformer
- No lockfile (source not queried)
- faster-whisper
- No published findings from this source as of 2026-07-11
Full report
- FasterTransformer
- Trust report
- faster-whisper
- Trust report
Choose FasterTransformer if…
- FasterTransformer is primarily C++; faster-whisper is Python.
- License: FasterTransformer is Apache-2.0, faster-whisper is MIT.
- Tags unique to FasterTransformer: bert, cublas, cublaslt, cuda.
- When aiming for high performance with GPU-based FP16 computations for BERT or GPT models specifically.
When NOT to use FasterTransformer
- If looking for active development and latest improvements on LLM Inference as NVIDIA recommends TensorRT-LLM over FasterTransformer now.
- When specific frameworks not including TensorFlow, PyTorch, or Triton are required.
Choose faster-whisper if…
- faster-whisper is primarily Python; FasterTransformer is C++.
- License: faster-whisper is MIT, FasterTransformer is Apache-2.0.
- Requirements: Requires Python 3.9 or higher.
- Tags unique to faster-whisper: deep-learning, inference, openai, quantization.
- Also covers Speech & Audio.
- A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2.
When NOT to use faster-whisper
- * When needing to employ FFmpeg directly for audio processing as it does not require FFmpeg installation and relies instead on PyAV.
- * In environments where additional dependencies from PyAV may introduce complexity or issues.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (NVIDIA/FasterTransformer) · observed Aug 7, 2026
- GitHub forks (NVIDIA/FasterTransformer) · observed Aug 7, 2026
- Last push (NVIDIA/FasterTransformer) · observed Mar 27, 2024
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (SYSTRAN/faster-whisper) · observed Aug 2, 2026
- GitHub forks (SYSTRAN/faster-whisper) · observed Aug 2, 2026
- Last push (SYSTRAN/faster-whisper) · observed Nov 19, 2025
- License file (MIT) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: FasterTransformer 6.4k · faster-whisper 25k (synced Aug 7, 2026).
Common questions
- What is the difference between FasterTransformer and faster-whisper?
- FasterTransformer: Transformer related optimization including BERT and GPT. faster-whisper: Faster Whisper transcription with CTranslate2. See the comparison table for live GitHub stats and shared categories.
- When should I choose FasterTransformer over faster-whisper?
- Choose FasterTransformer over faster-whisper when FasterTransformer is primarily C++; faster-whisper is Python; License: FasterTransformer is Apache-2.0, faster-whisper is MIT; Tags unique to FasterTransformer: bert, cublas, cublaslt, cuda; When aiming for high performance with GPU-based FP16 computations for BERT or GPT models specifically.
- When should I choose faster-whisper over FasterTransformer?
- Choose faster-whisper over FasterTransformer when faster-whisper is primarily Python; FasterTransformer is C++; License: faster-whisper is MIT, FasterTransformer is Apache-2.0; Requirements: Requires Python 3.9 or higher; Tags unique to faster-whisper: deep-learning, inference, openai, quantization; Also covers Speech & Audio; A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2.
- When should I avoid FasterTransformer?
- If looking for active development and latest improvements on LLM Inference as NVIDIA recommends TensorRT-LLM over FasterTransformer now. When specific frameworks not including TensorFlow, PyTorch, or Triton are required.
- When should I avoid faster-whisper?
- * When needing to employ FFmpeg directly for audio processing as it does not require FFmpeg installation and relies instead on PyAV. * In environments where additional dependencies from PyAV may introduce complexity or issues.
- Is FasterTransformer or faster-whisper more popular on GitHub?
- faster-whisper has more GitHub stars (24,689 vs 6,446). Stars measure visibility, not whether either tool fits your constraints.
- Are FasterTransformer and faster-whisper open source?
- Yes - both are open-source projects on GitHub (FasterTransformer: Apache-2.0, faster-whisper: MIT).
- Where can I find alternatives to FasterTransformer or faster-whisper?
- GraphCanon lists graph-backed alternatives at FasterTransformer alternatives and faster-whisper alternatives (FasterTransformer markdown twin, faster-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, FasterTransformer or faster-whisper?
- FasterTransformer: Dormant. faster-whisper: Slowing. 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 FasterTransformer and faster-whisper?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FasterTransformer trust report; faster-whisper trust report.