pythia-160m vs japanese-gpt-neox-small
Specs, VRAM requirements and download trends — updated 10 November 2026.
EleutherAI · A · Open weights
Params
210 M
Context
2,048
30d
3.5 M
apache-2.0 · commercial OK
rinna · B · Open weights
Params
200 M
Context
2,048
30d
520 K
mit · commercial OK
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | pythia-160m | japanese-gpt-neox-small |
|---|---|---|
| Parameters | 210 M | 200 M |
| Architecture | GPTNeoXForCausalLM | GPTNeoXForCausalLM |
| Context length | 2,048 | 2,048 |
| Licence | apache-2.0 | mit |
| Commercial use | Allowed | Allowed |
| Languages | 1 | 1 |
| Downloads 30d | 3,495,753 | 519,734 |
| Downloads all time | 32.2 M | 5.1 M |
| Quantizations on the Hub | SAFETENSORS | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2023-02-08 | 2022-08-31 |
Download trend
Daily snapshots, last 90 days (13 Aug – 10 Nov)
3.5 M375 K
pythia-160m
japanese-gpt-neox-small
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
pythia-160m · fp16
0.9 GB / 24 GB
japanese-gpt-neox-small · fp16
1.3 GB / 24 GB