Qwen3-0.6B vs Ternary-Bonsai-27B-mlx-2bit

Specs, VRAM requirements and download trends — updated 10 November 2026.

Qwen · A · Open weights
Params
750 M
Context
40,960
30d
20.7 M
apache-2.0 · commercial OK
prism-ml · B · Open weights
Params
2.6 B
Context
—
30d
1.0 M
apache-2.0 · commercial OK

Specification comparison

Differences are highlighted; identical values are muted.

Specification Qwen3-0.6B Ternary-Bonsai-27B-mlx-2bit
Parameters 750 M 2.6 B
Architecture Qwen3ForCausalLM Qwen3_5ForConditionalGeneration
Context length 40,960 —
Licence apache-2.0 apache-2.0
Commercial use Allowed Allowed
Languages — —
Downloads 30d 20,728,069 1,012,597
Downloads all time 261.3 M 4.7 M
Quantizations on the Hub SAFETENSORS SAFETENSORS
Gated No No
First seen on the Hub 2025-04-27 2026-07-04

Download trend

Daily snapshots, last 90 days (13 Aug – 10 Nov)

31.2 M962 K
Qwen3-0.6B Ternary-Bonsai-27B-mlx-2bit

VRAM side by side

On RTX 4090 · 24 GB · 8K context unless noted

Qwen3-0.6B · fp16 2.3 GB / 24 GB
✅ Runs comfortably
Ternary-Bonsai-27B-mlx-2bit · fp16 10.2 GB / 24 GB
✅ Runs comfortably

Adjacent comparisons