SAVRN Model Hub · Comparisons
Qwen3.5-2B vs Rax-4.5
Qwen3.5-2B has 2.3B parameters and Rax-4.5 has 2.3B parameters; both are released under Apache License 2.0; at 16-bit, Qwen3.5-2B needs about 5.5 GB (1x MI300X from $1.85 an hour) and Rax-4.5 about 5.5 GB (1x MI300X from $1.85 an hour).
| Field | Qwen3.5-2B Qwen/Qwen3.5-2B | Rax-4.5 raxcore-dev/Rax-4.5 |
|---|---|---|
| Publisher | Qwen | RaxCore |
| Task | Image and text to text | Image and text to text |
| Modality | Image and text | Image and text |
| Parameters, as reported | 2.3B parameters | 2.3B parameters |
| Architecture | Qwen3_5ForConditionalGeneration | Qwen3_5ForConditionalGeneration |
| Library | transformers | transformers |
| Context length | 262,144 tokens | 262,144 tokens |
| Repository size | 4.6 GB | 4.6 GB |
| Artifact formats | safetensors | safetensors |
| License | apache-2.0 | apache-2.0 |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 5.5 GB | 5.5 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 1.4 GB | 1.4 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 15852e8c1636 | 6ab58f792f61 |
| Downloads reported by the hub | 4.8M | 952.2k |
| 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.
Qwen3.5-2B
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| Idavidrein/gpqa | Task diamondMetric diamondSetup GPQA DiamondComparison conditions not established | 44.9495 | EvalEval Reported by a third party |
Evaluated revision not stated | 2026-04-20 |
| LiquidAI/ifstruct-v1.0 | Task ifstruct_v1Metric ifstruct_v1Comparison conditions not established | 33.15 | Liquid AI — IFStruct v1.0 blog (Qwen3.5-2B) Reported by a third party |
Evaluated revision not stated | 2026-06-30 |
| MMMU/MMMU_Pro | Task mmmu_pro_visionMetric mmmu_pro_visionSetup ThinkingComparison conditions not established | 50.3 | 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 | 55.3 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-03-02 |
| likaixin/ScreenSpot-Pro | Task overallMetric overallComparison conditions not established | 54.5 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-03-18 |
| llamaindex/ExtractBench | Task longMetric longSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 25.93 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task meanMetric meanSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 63.4 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task mediumMetric mediumSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 50.93 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task shortMetric shortSetup Pipeline name: qwen3_5_2b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 71.22 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
| llamaindex/ParseBench | Task chartMetric chartSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 0.1 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task layoutMetric layoutSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 18.3 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task meanMetric meanSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 27.3 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task tableMetric tableSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 0 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task text_contentMetric text_contentSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 87.2 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-22 |
| llamaindex/ParseBench | Task text_formattingMetric text_formattingSetup Pipeline name: qwen3_5_2b_vllm_layoutComparison conditions not established | 31.1 | ParseBench Reported by a third party |
Evaluated revision not stated | 2026-04-22 |
SAVRN's Notes on Qwen3.5-2B
We would size this one by its context window rather than its weights. The 2.3B parameters need 5.5 GB at 16-bit, 2.7 GB at 8-bit and 1.4 GB at 4-bit, so on the cheapest Index setup, one MI300X with 192 GB at $1.85 an hour on-demand, the weights take a sliver of the card and the 262,144-token context fills the rest. It takes images and text in and returns text, and the footprint buys many concurrent copies or one copy holding long inputs.
Apache 2.0 covers commercial use, modification and redistribution, with notices kept, significant changes stated and a patent grant included. Two checks: the page records a derivation from Qwen/Qwen3.5-2B-Base, so decide whether you want that base for your own post-training or this release, and no Index host prices it by the token yet, so the $1.85 hourly card is the number to run your volume against.
SAVRN's Notes on Rax-4.5
A context window of 262,144 tokens on 2.3 billion parameters, taking image and text in and producing text. At 16-bit the weights are 4.5 GB and the run needs 5.5 GB of memory; 8-bit brings that to 2.7 GB and 4-bit to 1.4 GB. Any of those fits on the cheapest card in our table, one MI300X with 192 GB at $1.85 an hour on demand, and the spare room matters: a filled context window adds memory on top of the weights.
RaxCore publishes it under Apache 2.0, so commercial use, modification and redistribution are allowed with the notices retained. The architecture is listed as Qwen3_5ForConditionalGeneration, yet the only relation on record points back to Rax-4.5 itself, so ask the publisher what base model and data sit underneath. No SAVRN Index host serves it by the token yet, so self-hosting is the only price we can quote. Released November 27, 2025 and last updated July 13, 2026.
Questions
Which is larger, Qwen3.5-2B or Rax-4.5?
Qwen3.5-2B (2.3B parameters) is larger than Rax-4.5 (2.3B parameters), by the parameter counts their publishers report.
Which is cheaper to run, Qwen3.5-2B or Rax-4.5?
At 4-bit, Qwen3.5-2B fits on 1x MI300X from $1.85 an hour and Rax-4.5 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use Qwen3.5-2B commercially?
Yes. Qwen3.5-2B 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 Rax-4.5 commercially?
Yes. Rax-4.5 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.