Qwen3-1.7B vs gpt2-large
Specs, VRAM requirements and download trends — updated 6 August 2026.
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | Qwen3-1.7B | gpt2-large |
|---|---|---|
| Parameters | 2.0 B | 810 M |
| Architecture | Qwen3ForCausalLM | GPT2LMHeadModel |
| Context length | 40,960 | — |
| Licence | apache-2.0 | mit |
| Commercial use | Allowed | Allowed |
| Languages | — | 1 |
| Downloads 30d | 7,765,125 | 1,489,219 |
| Downloads all time | 56.3 M | 58.8 M |
| Quantizations on the Hub | SAFETENSORS | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2025-04-27 | 2022-03-02 |
Download trend
Daily snapshots, last 10 days (28 Jul – 6 Aug)
7.8 M1.5 M
Qwen3-1.7B
gpt2-large
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
gpt2-large · fp16
4.2 GB / 24 GB
Qwen3-1.7B · fp16
5.3 GB / 24 GB