by Nex Agi

Nex-N2.5-Mini.

multimodal open weights workstation 35B params 262K ctx
Cheapest input
$0.025/M
on OpenRouter
Cheapest output
$0.1/M
on OpenRouter
Smallest GPU
1× Nvidia GeForce RTX 3090
$0.15/hr
Run it yourself

Cheapest hardware per quantisation.

Each row is one quantisation tier (the same weights compressed differently). Lower precision → lower VRAM → cheaper hardware, at the cost of small accuracy loss. $/hr is the cheapest rate on offer now. A multi-card setup uses a real instance of that size when one is rented; otherwise it is the single-card rate times the count.

Quantisation Cheapest GPU config Total VRAM Live $/hr tokens/sec
FP16
FP16 — half precision (default)
96 GB $0.52/hr
est. 2 × single-card rate
Vast.ai · on-demand
— Compare →
FP8
FP8 — 8-bit float (Hopper / Blackwell)
48 GB $0.26/hr
Vast.ai · on-demand
13.4 Compare →
INT4
INT4 — 4-bit integer (~4× VRAM saving)
24 GB $0.15/hr
Akash Network · token-paid
37.3 Compare →
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