The largest decider model: a mixture-of-experts fine-tune of Qwen3.5-35B-A3B with about 3B parameters active per token. It answers Choice, Score and Noul questions with calibrated probabilities in one forward pass. An NVFP4 build for Blackwell GPUs is published alongside it.
A workable 34.66B-parameter MoE decision model from Mapika. 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 | 3.0 GB |
| Acer Veriton GN100 AI MiniAcer | SS | 3.0 GB |
| AMD Instinct MI300XAMD | SS | 3.0 GB |
| AMD Instinct MI325XAMD | SS | 3.0 GB |
| AMD Instinct MI355XAMD | SS | 3.0 GB |
Cheapest current cloud rentals with at least 3 GB VRAM, refreshed hourly.
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| Option | Cost / GPU-hour |
|---|---|
NVIDIA Tesla V100 16GBVast.ai · Spot · 16 GB VRAM | $0.05 |
NVIDIA GeForce RTX 3090Vast.ai · Spot · 24 GB VRAM | $0.07 |
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 |
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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