SAVRN Model Hub · Comparisons
gpt2-large vs Qwen2.5-0.5B-Instruct
Gpt2-large has 812M parameters and Qwen2.5-0.5B-Instruct has 494M parameters; gpt2-large is released under MIT License and Qwen2.5-0.5B-Instruct under Apache License 2.0; at 16-bit, gpt2-large needs about 1.9 GB (1x MI300X from $1.85 an hour) and Qwen2.5-0.5B-Instruct about 1.2 GB (1x MI300X from $1.85 an hour).
| Field | gpt2-large openai-community/gpt2-large | Qwen2.5-0.5B-Instruct Qwen/Qwen2.5-0.5B-Instruct |
|---|---|---|
| Publisher | OpenAI community | Qwen |
| Task | Text generation | Text generation |
| Modality | Text | Text |
| Parameters, as reported | 812M parameters | 494M parameters |
| Architecture | GPT2LMHeadModel | Qwen2ForCausalLM |
| Library | transformers | transformers |
| Context length | Not stated | 32,768 tokens |
| Repository size | 26.3 GB | 999.6 MB |
| Artifact formats | safetensors, onnx, pytorch, jax, rust, tf | safetensors |
| License | mit | apache-2.0 |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 1.9 GB | 1.2 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 0.5 GB | 0.3 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 32b71b12589c | 7ae557604adf |
| Downloads reported by the hub | 1.2M | 8.5M |
| Last observed | 2026-09-18 | 2026-09-18 |
An evaluation row appears only where at least two of these models report the same benchmark with the same stated configuration, metric, unit and setup. Different evaluators stay named in each cell. Values are shown as reported: no unit conversion, no ranking.
SAVRN's Notes on gpt2-large
Published March 2, 2022, this English causal language model moves 1,243,231 downloads a month. The configuration counts 812M parameters; the publisher says 774M. At 16-bit the weights are 1.6 GB and need 1.9 GB, 8-bit needs 1.0 GB and 4-bit 0.5 GB, so the cheapest host in our data, one MI300X with 192 GB at $1.85 per hour, is far more card than it needs. Prove a pipeline on it, then move the real workload in.
MIT is a short permissive license: keep the copyright and permission notice and you can use, modify and redistribute it commercially. Our facts record no context length for it, so confirm the window in the configuration you load. The repository totals 26.3 GB across 29 files because it ships six formats, and the one paper it cites, arXiv:1910.09700, covers the carbon emissions of machine learning, not this model.
SAVRN's Notes on Qwen2.5-0.5B-Instruct
Run this one at 16-bit and it asks for 1.2 GB of memory; 8-bit needs 0.6 GB and 4-bit 0.3 GB. The cheapest setup we list is a single 192 GB MI300X at $1.85 per hour on-demand, and we would not give 494M parameters a card of their own. It belongs on shared capacity beside larger jobs, where its 32,768 token context still covers the table reading and JSON output Qwen highlighted for the 2.5 series.
Apache 2.0 keeps the deployment simple: commercial use, modification and redistribution, provided the license, notices and NOTICE file stay attached and significant changes are stated. Two checks before committing. It was derived from the Qwen2.5-0.5B base, so if the instruct tuning does not fit, tune the base yourself. Our Index has no per-token host price for it, so that hourly card is the only cost signal, on weights last updated September 25, 2024.
Questions
Which is larger, gpt2-large or Qwen2.5-0.5B-Instruct?
gpt2-large (812M parameters) is larger than Qwen2.5-0.5B-Instruct (494M parameters), by the parameter counts their publishers report.
Which is cheaper to run, gpt2-large or Qwen2.5-0.5B-Instruct?
At 4-bit, gpt2-large fits on 1x MI300X from $1.85 an hour and Qwen2.5-0.5B-Instruct on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use gpt2-large commercially?
Yes. gpt2-large is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.
Can I use Qwen2.5-0.5B-Instruct commercially?
Yes. Qwen2.5-0.5B-Instruct is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.