ExLlamaV3 v0.0.33 Adds Gemma 4 Support, DFlash Speedups, and Model Optimizations
Upgrade to ExLlamaV3 v0.0.33 to leverage Gemma 4 support, DFlash speedups, and new model optimizations.
Update your ExLlamaV3 installation to v0.0.33 and run benchmarks on your target models.
Summary
ExLlamaV3 has released a major update to v0.0.33, adding several new features and optimizations. The release builds on earlier versions that added Gemma 4 support (v0.0.29) and improved caching (v0.0.30). Version 0.0.31 introduced DFlash support, delivering up to 2.51× speedups on the Agentic, code category and 3.00× on Coding. Version 0.0.32 added model‑level optimizations, showing percentage reductions for Qwen3.5‑35B‑A3B‑UD‑Q3_K_S and other models across various GPUs.
The latest release, v0.0.33, adds DFlash model quantization, further bug fixes, and efficiency improvements. DFlash results include 140.61 t/s for Agentic, code (2.51×) and 177.67 t/s for Coding (3.00×). The author also invites readers to join the ExLlama Discord community for support and discussion.
Overall, the update provides significant performance gains for a range of LLMs and expands the library’s compatibility with newer models.
Key changes
- v0.0.29 added Gemma 4 support
- v0.0.30 improved caching efficiency
- v0.0.31 added DFlash support with 2.51× speedup on Agentic, code
- v0.0.32 added model‑level optimizations with percentage reductions for Qwen3.5‑35B‑A3B‑UD‑Q3_K_S
- v0.0.33 added DFlash model quantization and bug fixes
- DFlash results: 140.61 t/s for Agentic, code (2.51×) and 177.67 t/s for Coding (3.00×)
- Discord community for support