Tev1 4B Experimental.
1× Nvidia RTX A2000 Laptop GPU.
Most-aggressive quantisation we have a working recommendation for. Lower precision = less VRAM = cheaper hardware, at a small accuracy cost.
Cheapest hosted endpoints.
| Provider | Access | $/M in | $/M out | |
|---|---|---|---|---|
| Together AI | hosted inference | $0.042 | $0.0 | Launch ↗ |
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)
|
16 GB |
$0.019/hr
Clore.ai · on-demand
|
24.0 | Compare → | |
|
FP8
FP8 — 8-bit float (Hopper / Blackwell)
|
8 GB |
$0.022/hr
Clore.ai · on-demand
|
33.6 | Compare → | |
|
INT4
INT4 — 4-bit integer (~4× VRAM saving)
|
4 GB | — | 57.7 | Compare → |
What it costs per month across providers.
Estimate your monthly bill for Tev1 4B Experimental across every host that publishes per-token pricing. Slide your token volumes; the chart + table re-rank cheapest-first.
Cheapest provider on the left.
Total monthly cost — input + output tokens combined.
Bill breakdown.
| Provider | Monthly total | |
|---|---|---|
| $0.42 | Sign up ↗ |
Rent the GPU instead of paying per token.
For an open-weights model like Tev1 4B Experimental, you can rent a GPU and serve inference yourself. The math: cheapest GPU rental × 730 hours/month. Power is included in a rental's hourly price.
Assumes the GPU runs 24/7 at ~85% utilisation. If your traffic is bursty, you'll pay less for the API and probably more for the GPU (idle hours still cost rental). The breakeven analysis lives on the Self-host vs API breakeven tool.