GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 vs colibrì — tiny engine, immense model
GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 vs colibrì — tiny engine, immense model: both are strong options for artificial intelligence. GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 is best for developers and researchers needing to run massive models on limited hardware, while colibrì — tiny engine, immense model suits ai researchers and developers who want to study and improve large moe models on consumer hardware.. Below is the full side-by-side on features, pricing and who each fits best.
GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦Colibri is an impressive technical achievement that makes massive MoE models accessible on consumer hardware, though with some trade-offs in exact output consistency.
Pick it if: The only solution that can run 744B parameter models on consumer-grade hardware with pure C.
colibrì — tiny engine, immense modelcolibrì is a groundbreaking tool for AI researchers and developers, offering unprecedented access to frontier-class models on consumer hardware. Its transparency and efficiency make it a must-try for those in the field.
Pick it if: It uniquely enables running and studying 744B MoE models on consumer hardware with full transparency.
| GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 | colibrì — tiny engine, immense model | |
|---|---|---|
| Category | Artificial Intelligence | Artificial Intelligence |
| Score | 4.5/5 | 4.5/5 |
| Pricing | open-source | open-source |
| Public API | ✕ No | ✕ No |
| Free tier | ✓ Yes | ✓ Yes |
| Self-host | ✓ Yes | ✓ Yes |
| Platforms | Linux, macOS, Windows | Linux, Windows, macOS |
| Best for | Developers and researchers needing to run massive models on limited hardware | AI researchers and developers who want to study and improve large MoE models on consumer hardware. |
| Not ideal for | Those needing byte-exact reproducibility or who don't have sufficient disk space for the expert files. | Casual users or those without technical expertise in AI and machine learning. |
GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦
- Extremely efficient memory usage for large models
- No dependencies - simple deployment
- Validated against transformers for accuracy
- Not byte-identical to non-speculative greedy in practice
- Requires significant disk space (~370GB for experts)
colibrì — tiny engine, immense model
- Runs frontier-class models on consumer hardware
- Transparent and open for study and improvement
- Efficient use of hardware resources
- Requires technical expertise to modify and optimize
- Performance may vary based on hardware configuration
Frequently asked questions
Is GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 better than colibrì — tiny engine, immense model?
The only solution that can run 744B parameter models on consumer-grade hardware with pure C.. colibrì — tiny engine, immense model: It uniquely enables running and studying 744B MoE models on consumer hardware with full transparency.
What's the main difference between GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 and colibrì — tiny engine, immense model?
GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 is a artificial intelligence tool best for developers and researchers needing to run massive models on limited hardware. colibrì — tiny eng
Which is cheaper, GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 or colibrì — tiny engine, immense model?
GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦: open-source. colibrì — tiny engine, immense model: open-source. Both offer a free tier.
Can I self-host GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦 or colibrì — tiny engine, immense model?
GitHub - JustVugg/colibri: Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦: yes, self-hosting is supported. colibrì — tiny engine, immense model: yes, self-hosting is supported.