SAVRN Model Hub · Comparisons
gemma-4-12B-it vs Qwen2.5-Omni-7B
Gemma-4-12B-it has 12B parameters and Qwen2.5-Omni-7B has 10.7B parameters; gemma-4-12B-it is released under Apache License 2.0 and Qwen2.5-Omni-7B under other; at 16-bit, gemma-4-12B-it needs about 28.7 GB (1x MI300X from $1.85 an hour) and Qwen2.5-Omni-7B about 25.8 GB (1x MI300X from $1.85 an hour).
| Field | gemma-4-12B-it google/gemma-4-12B-it | Qwen2.5-Omni-7B Qwen/Qwen2.5-Omni-7B |
|---|---|---|
| Publisher | Qwen | |
| Task | Any to any | Any to any |
| Modality | Multimodal | Multimodal |
| Parameters, as reported | 12B parameters | 10.7B parameters |
| Architecture | Gemma4UnifiedForConditionalGeneration | Qwen2_5OmniModel |
| Library | transformers | transformers |
| Context length | 262,144 tokens | Not stated |
| Repository size | 24.0 GB | 22.4 GB |
| Artifact formats | safetensors | safetensors |
| License | apache-2.0 | other |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 28.7 GB | 25.8 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 7.2 GB | 6.4 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 707f0a3b8a3c | ae9e1690543f |
| Downloads reported by the hub | 2.7M | 347.6k |
| 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.
gemma-4-12B-it
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| Idavidrein/gpqa | Task diamondMetric diamondComparison conditions not established | 78.8 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-05-23 |
| MMMU/MMMU_Pro | Task mmmu_proMetric mmmu_proComparison conditions not established | 69.1 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-05-23 |
| MathArena/aime_2026 | Task MathArena/aime_2026Metric MathArena/aime_2026Setup No toolsComparison conditions not established | 77.5 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-05-23 |
| TIGER-Lab/MMLU-Pro | Task mmlu_proMetric mmlu_proComparison conditions not established | 77.2 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-05-23 |
| cais/hle | Task hleMetric hleSetup No toolsComparison conditions not established | 5.2 | Model Card Reported by a third party |
Evaluated revision not stated | 2026-05-23 |
| llamaindex/ExtractBench | Task longMetric longSetup Pipeline name: gemma4_12b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 13.16 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task meanMetric meanSetup Pipeline name: gemma4_12b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 45.39 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task mediumMetric mediumSetup Pipeline name: gemma4_12b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 30.82 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
| llamaindex/ExtractBench | Task shortMetric shortSetup Pipeline name: gemma4_12b_vllm_extract_oneshot_structured_output_fileComparison conditions not established | 53.62 | ExtractBench Reported by a third party |
Evaluated revision not stated | 2026-08-24 |
SAVRN's Notes on gemma-4-12B-it
Text and images in, audio too on this size, text out, 140-plus languages, a 256K-token window: that is Google's instruction-tuned Gemma 4 12B. The footprint is 28.7 GB at 16-bit, 14.4 GB at 8-bit and 7.2 GB at 4-bit, all three on one MI300X at $1.85 per hour with 192 GB to work in, so the question is not which card but how much of it you leave for a 262,144-token context and its neighbors.
Nothing in Apache 2.0 stops you: commercial use, modification and redistribution, with license and NOTICE files kept and changes stated. It derives from google/gemma-4-12B, the pre-trained base, so start there for your own tuning, and read arXiv:2607.02770 first. The scores here, 78.8 on GPQA diamond among them, are model card numbers, not ours; run your own documents. No Index host prices it by the token; the comparison is the card hour.
Questions
Which is larger, gemma-4-12B-it or Qwen2.5-Omni-7B?
gemma-4-12B-it (12B parameters) is larger than Qwen2.5-Omni-7B (10.7B parameters), by the parameter counts their publishers report.
Which is cheaper to run, gemma-4-12B-it or Qwen2.5-Omni-7B?
At 4-bit, gemma-4-12B-it fits on 1x MI300X from $1.85 an hour and Qwen2.5-Omni-7B on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use gemma-4-12B-it commercially?
Yes. gemma-4-12B-it 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.