Ternary-Bonsai-27B-mlx-2bit vs Qwen2.5-Math-1.5B
Specs, VRAM requirements and download trends — updated 4 September 2026.
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | Ternary-Bonsai-27B-mlx-2bit | Qwen2.5-Math-1.5B |
|---|---|---|
| Parameters | 2.6 B | 1.5 B |
| Architecture | Qwen3_5ForConditionalGeneration | Qwen2ForCausalLM |
| Context length | — | 4,096 |
| Licence | apache-2.0 | apache-2.0 |
| Commercial use | Allowed | Allowed |
| Languages | — | 1 |
| Downloads 30d | 1,065,043 | 207,749 |
| Downloads all time | 2.9 M | 7.2 M |
| Quantizations on the Hub | SAFETENSORS | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2026-07-04 | 2024-09-16 |
Download trend
Daily snapshots, last 50 days (3 Aug – 21 Sep)
2.1 M197 K
Ternary-Bonsai-27B-mlx-2bit
Qwen2.5-Math-1.5B
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
Qwen2.5-Math-1.5B · fp16
4.1 GB / 24 GB
Ternary-Bonsai-27B-mlx-2bit · fp16
10.2 GB / 24 GB