SAVRN Model Hub · Comparisons
Qwen3-4B vs xflux_text_encoders
Qwen3-4B has 4B parameters and xflux_text_encoders has 4.8B parameters; both are released under Apache License 2.0; at 16-bit, Qwen3-4B needs about 9.7 GB (1x MI300X from $1.85 an hour) and xflux_text_encoders about 11.4 GB (1x MI300X from $1.85 an hour).
| Field | Qwen3-4B Qwen/Qwen3-4B | xflux_text_encoders XLabs-AI/xflux_text_encoders |
|---|---|---|
| Publisher | Qwen | XLabs AI |
| Task | Text generation | Text generation |
| Modality | Text | Text |
| Parameters, as reported | 4B parameters | 4.8B parameters |
| Architecture | Qwen3ForCausalLM | T5EncoderModel |
| Library | transformers | transformers |
| Context length | 40,960 tokens | Not stated |
| Repository size | 8.1 GB | 9.5 GB |
| Artifact formats | safetensors | safetensors, pytorch |
| License | apache-2.0 | apache-2.0 |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 9.7 GB | 11.4 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 2.4 GB | 2.9 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 1cfa9a720891 | 5ce032c6b9bf |
| Downloads reported by the hub | 6.9M | 320.5k |
| Last observed | 2026-09-21 | 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 Qwen3-4B
Memory is not the constraint with Qwen3-4B. The 16-bit weights are 8.0 GB and need 9.7 GB to serve, 8-bit needs 4.8 GB and 4-bit 2.4 GB, so on the cheapest Index setup, one MI300X with 192 GB at $1.85 an hour, the card sits mostly empty and the decision is how many copies to run. It is text only, switches between a thinking mode and a plain dialogue mode, and carries a 40,960-token context.
Apache 2.0 lets you fine-tune it, ship it in a product and charge for it, provided the license and notices travel with it and you state what you changed. Before you commit, look at the lineage and the price sheet: it is derived from Qwen3-4B-Base, so decide whether you want this release or the base for post-training, and the page lists no Index host prices, so there is nothing per token to compare with.
Questions
Which is larger, Qwen3-4B or xflux_text_encoders?
xflux_text_encoders (4.8B parameters) is larger than Qwen3-4B (4B parameters), by the parameter counts their publishers report.
Which is cheaper to run, Qwen3-4B or xflux_text_encoders?
At 4-bit, Qwen3-4B fits on 1x MI300X from $1.85 an hour and xflux_text_encoders on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use Qwen3-4B commercially?
Yes. Qwen3-4B 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.
Can I use xflux_text_encoders commercially?
Yes. xflux_text_encoders 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.