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A multimodal decision model on Gemma 4 12B that answers questions about text, images, audio and video with a probability for each option. It adds a trained decision head that accepts up to 256 options, though quality is only established up to 20. Text decisions take about 83 ms on an H200.
A workable 11.96B-parameter dense decision model from akhilaaa3. Treat the modality benchmarks above as the leading indicator of fit — composite scoring across modalities is still maturing. Newly released, so production-readiness is still being shaken out.
Generated from this model’s benchmarks and ranking signals. Editor reviews refine it over time.
Access model weights, configuration files, and documentation.
The top devices for this model at 4-bit, ranked by fit and speed.
| Device | Grade | VRAM |
|---|---|---|
| ACEMAGIC M1A Pro (i9-13900HK + ARC A770)ACEMAGIC | SS | 7.8 GB |
| Acer Veriton GN100 AI MiniAcer | SS | 7.8 GB |
| AMD Instinct MI300XAMD | SS | 7.8 GB |
| AMD Instinct MI325XAMD | SS | 7.8 GB |
| AMD Instinct MI355XAMD | SS | 7.8 GB |
Cheapest current cloud rentals with at least 8 GB VRAM, refreshed hourly.
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| Option | Cost / GPU-hour |
|---|---|
NVIDIA Tesla V100 16GBVast.ai · Spot · 16 GB VRAM | $0.04 |
NVIDIA GeForce RTX 5060 TiVast.ai · Spot · 16 GB VRAM | $0.07 |
NVIDIA GeForce RTX 4060 TiVast.ai · Spot · 8 GB VRAM | $0.07 |
NVIDIA GeForce RTX 4070Vast.ai · Spot · 12 GB VRAM | $0.08 |
NVIDIA Tesla V100 16GBVast.ai · On-Demand · 16 GB VRAM | $0.08 |
Per-GPU rate across RunPod, the Vast.ai marketplace, DigitalOcean, and Vultr.
Spot tier is interruptible. Plan for restarts when comparing against on-demand prices.
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