SAVRN Model Hub · Comparisons
Qwen3.5-4B vs vllm-translategemma-4b-it
Qwen3.5-4B has 4.7B parameters and vllm-translategemma-4b-it has 5B parameters; Qwen3.5-4B is released under Apache License 2.0 and vllm-translategemma-4b-it under Gemma Terms of Use; at 16-bit, Qwen3.5-4B needs about 11.2 GB (1x MI300X from $1.85 an hour) and vllm-translategemma-4b-it about 11.9 GB (1x MI300X from $1.85 an hour).
| Field | Qwen3.5-4B Qwen/Qwen3.5-4B | vllm-translategemma-4b-it Infomaniak-AI/vllm-translategemma-4b-it |
|---|---|---|
| Publisher | Qwen | Infomaniak Network SA |
| Task | Image and text to text | Image and text to text |
| Modality | Image and text | Image and text |
| Parameters, as reported | 4.7B parameters | 5B parameters |
| Architecture | Qwen3_5ForConditionalGeneration | Gemma3ForConditionalGeneration |
| Library | transformers | transformers |
| Context length | 262,144 tokens | 131,072 tokens |
| Repository size | 9.3 GB | 8.6 GB |
| Artifact formats | safetensors | safetensors |
| License | apache-2.0 | gemma |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 11.2 GB | 11.9 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 2.8 GB | 3 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 851bf6e806ef | cb3e0b2504f0 |
| Downloads reported by the hub | 7M | 743.2k |
| 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.
Other Reported Results
These results are listed for each model on its own, because the conditions needed to compare them are not stated or do not match. Two results that leave a condition blank are not assumed to share it.
Qwen3.5-4B
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| Idavidrein/gpqa | Task diamondMetric diamondComparison conditions not established | 76.2 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-03-02 |
| LiquidAI/ifstruct-v1.0 | Task ifstruct_v1Metric ifstruct_v1Comparison conditions not established | 36.25 | Liquid AI — IFStruct v1.0 blog (Qwen3.5-4B) Reported by a third party |
Evaluated revision not stated | 2026-06-30 |
| MMMU/MMMU_Pro | Task mmmu_pro_visionMetric mmmu_pro_visionComparison conditions not established | 66.3 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-04-28 |
| TIGER-Lab/MMLU-Pro | Task mmlu_proMetric mmlu_proComparison conditions not established | 79.1 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-03-02 |
| likaixin/ScreenSpot-Pro | Task overallMetric overallComparison conditions not established | 60.3 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-03-18 |
| llamaindex/ExtractBench | Task longMetric longSetup Pipeline name: qwen3_5_4b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 27.31 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-26 |
| llamaindex/ExtractBench | Task meanMetric meanSetup Pipeline name: qwen3_5_4b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 82.43 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-26 |
| llamaindex/ExtractBench | Task mediumMetric mediumSetup Pipeline name: qwen3_5_4b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 76.64 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-26 |
| llamaindex/ExtractBench | Task shortMetric shortSetup Pipeline name: qwen3_5_4b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 89.06 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-26 |
| llamaindex/ParseBench | Task chartMetric chartSetup Pipeline name: qwen3_5_4b_vllm_layoutComparison conditions not established | 2.5 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-14 |
| llamaindex/ParseBench | Task layoutMetric layoutSetup Pipeline name: qwen3_5_4b_vllm_layoutComparison conditions not established | 19.7 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-14 |
| llamaindex/ParseBench | Task meanMetric meanSetup Pipeline name: qwen3_5_4b_vllm_layoutComparison conditions not established | 35.4 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-14 |
| llamaindex/ParseBench | Task tableMetric tableSetup Pipeline name: qwen3_5_4b_vllm_layoutComparison conditions not established | 8 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-14 |
| llamaindex/ParseBench | Task text_contentMetric text_contentSetup Pipeline name: qwen3_5_4b_vllm_layoutComparison conditions not established | 88.9 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-14 |
| llamaindex/ParseBench | Task text_formattingMetric text_formattingSetup Pipeline name: qwen3_5_4b_vllm_layoutComparison conditions not established | 57.8 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-14 |
SAVRN's Notes on Qwen3.5-4B
A 262,144-token window on a 4.7B model shapes everything else here. It is built on Qwen3.5-4B-Base and reads images as well as text. At 16-bit it needs 11.2 GB to run, so on the cheapest setup we list, one MI300X with 192 GB at $1.85 an hour on demand, quantizing is a choice, not a requirement; 4-bit brings it to 2.8 GB for several copies on one card.
Apache 2.0 means you can run it commercially, fine-tune it and redistribute what you make, as long as the license and any NOTICE file stay attached and you state significant changes, with a patent grant included. Before committing, run the window length you intend to use and measure memory there; 11.2 GB is the entry ticket, not the ceiling. Released February 27, 2026, it is young; check the publisher's page for revisions before you freeze a version.
SAVRN's Notes on vllm-translategemma-4b-it
Infomaniak Network SA published this, not Google. It is google/translategemma-4b-it with the chat template rewritten so vLLM can take the source and target language codes inline in the message, marked by double arrows, rather than in separate fields. Image and text in, text out, 5 billion parameters, a 131,072-token window with a 1,024-token sliding window. The 16-bit weights are 9.9 GB and need 11.9 GB; 8-bit needs 6.0 GB and 4-bit needs 3.0 GB. The cheapest fit we list is one MI300X with 192 GB at $1.85 an hour.
The Gemma Terms of Use govern it whoever re-hosts the weights: commercial use is allowed provided the Prohibited Use Policy travels with every copy you pass on, so redistribution carries paperwork that an internal deployment does not. Confirm your serving stack honors the modified template, and know that our file holds no evaluations for it and no host prices.
Questions
Which is larger, Qwen3.5-4B or vllm-translategemma-4b-it?
vllm-translategemma-4b-it (5B parameters) is larger than Qwen3.5-4B (4.7B parameters), by the parameter counts their publishers report.
Which is cheaper to run, Qwen3.5-4B or vllm-translategemma-4b-it?
At 4-bit, Qwen3.5-4B fits on 1x MI300X from $1.85 an hour and vllm-translategemma-4b-it on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use Qwen3.5-4B commercially?
Yes. Qwen3.5-4B 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 vllm-translategemma-4b-it commercially?
Yes, with conditions. vllm-translategemma-4b-it is released under Gemma Terms of Use. Gemma models are released under Google's Gemma Terms of Use, which permit commercial use and redistribution subject to the Gemma Prohibited Use Policy, whose restrictions must be passed on to anyone the model is distributed to.