A LoRA adapter and scoring head on Google’s Gemma 3 270M that scores all options of a Choice, Score or yes/no question in one pass. Trained in about 15 minutes on a free Colab GPU; the bundled weights carry a non-commercial restriction from their training data.
A niche 0.27B-parameter dense decision model from Akash Kamat. 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.
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 | 0.7 GB |
| Acer Veriton GN100 AI MiniAcer | SS | 0.7 GB |
| AMD Instinct MI300XAMD | SS | 0.7 GB |
| AMD Instinct MI325XAMD | SS | 0.7 GB |
| AMD Instinct MI355XAMD | SS | 0.7 GB |

Explore the Provider
Aggregate stats, leaderboard, release timeline, and benchmark coverage across every Akash Kamat model we track.
Cheapest current cloud rentals with at least 1 GB VRAM, refreshed hourly.
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| Option | Cost / GPU-hour |
|---|---|
NVIDIA GeForce RTX 4060Vast.ai · Spot · 8 GB VRAM | $0.03 |
NVIDIA GeForce RTX 2080 TiVast.ai · Spot · 11 GB VRAM | $0.04 |
NVIDIA GeForce RTX 3070Vast.ai · Spot · 8 GB VRAM | $0.05 |
NVIDIA GeForce RTX 3060Vast.ai · Spot · 12 GB VRAM | $0.05 |
NVIDIA GeForce RTX 4060 TiVast.ai · Spot · 8 GB VRAM | $0.05 |
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.