GEV-26B-Decide
enthusiastThe Jev recipe on a Gemma spine, at open-source velocity. GEV-26B-Decide is AutoTrust’s decision model on Google’s Gemma 4 26B backbone (A4B: 4B of it active at inference): image or text in, one probability score per allowed action out, one forward pass. 903,866 downloads and 1,588 likes in under a week on Hugging Face, Apache 2.0.
The base-family bet. The decision-model wave’s first generation all tuned Qwen backbones; GEV ports the recipe to Gemma and the same team ships JEV-27B-VL on Qwen with vision, so the two base families can be compared on the same task set. For deployment the Gemma port matters commercially: Gemma’s license terms are the lightest of the major bases for self-hosting at fleet scale, and the A4B active count means per-token compute is a quarter of the parameter count, so serving cost tracks roughly 4B-class even though 25.8GB of weights stay resident in 4-bit.
What runs where. 14.8GB of q4 weights plus a KV cache of 240MB per 1,000 tokens (30 layers x 8 kv-heads x 256 dim): a 24GB card serves routing-scale contexts comfortably, and a 384GB unified cluster (the 512GB Ultra tier) holds the whole 262k context with the KV ledger closed.
- 25.8B
- 262k
- apache 2.0
- 🇺🇸 USA
- Oct 2026
Guides covering GEV-26B-Decide
Save your hardware and every model page answers the real question: will it run on your machine, and how fast?
Join free - save your rig →Run it locally
Per-quant memory needs and a static "can you run it?" reference - no rig entry required
The reference hardware
22 reference configs, drawn in-house. Scroll for more.
Can you run it? - reference rigs
| Rig | Q4_K_M | FP16 |
|---|---|---|
| NVIDIA Jetson Orin NX 16GB | tight | no -> cloud |
| Single GTX 1080 Ti (11GB) | offload | no -> cloud |
| 4x H100 80GB (320GB) | fast 467.6t/s | fast 140.2t/s |
| NVIDIA DGX Station 748GB | fast 279.2t/s | fast 83.7t/s |
| 8x RTX 3090 rack (192GB) | fast 261.4t/s | fast 78.4t/s |
| 4x RTX 5090 (128GB) | fast 250.2t/s | fast 75.0t/s |
| AMD Instinct MI300X (192GB) | fast 185.8t/s | fast 55.7t/s |
| 4x RTX 4090 (96GB) | fast 140.7t/s | fast 42.2t/s |
| 2x RTX 5090 (64GB) | fast 125.1t/s | fast 37.5t/s |
| 2x RTX 3090 (48GB) | fast 65.3t/s | offload |
| Single RTX 5090 (32GB) | fast 62.5t/s | offload |
| RTX PRO 6000 Blackwell (96GB) | fast 62.5t/s | ok 18.8t/s |
| Mac Studio M4 Ultra 192GB | fast 41.6t/s | ok 12.5t/s |
| Mac Studio M4 Ultra 512GB | fast 41.6t/s | ok 12.5t/s |
| Single RTX 4090 (24GB) | fast 35.2t/s | no -> cloud |
| MacBook Pro M5 Max 128GB | fast 23.4t/s | slow 7.0t/s |
| Dual EPYC 9004 + 768GB DDR5-4800 | ok 16.1t/s | slow 4.8t/s |
| DGX Spark 128GB unified | ok 9.5t/s | slow 2.9t/s |
| Ryzen AI Max+ 395 128GB | ok 8.9t/s | slow 2.7t/s |
| Jetson AGX Orin 64GB | slow 7.2t/s | slow 2.1t/s |
| Epyc + 512GB DDR4-3200 + 2x RTX 3090 | slow 7.2t/s | slow 2.1t/s |
| Epyc + 512GB DDR4-2400 + 2x RTX 3090 | slow 5.4t/s | slow 1.6t/s |
Fit tiers use the same will-it-run logic as the rig finder. For comfortable fits, the badge reflects decode speed: fast >=20 t/s, ok 8-20 t/s, slow <8 t/s. t/s is a bandwidth estimate, not a measured benchmark.
Download options
Or run it in the cloud
No per-token API provider pricing tracked for GEV-26B-Decide yet. For flagship list prices, see the calculator.
Inference cost over time
Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.