Meta: Muse Spark Open.
Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and deep codebase understanding across the rep
4× AMD MI300X · $2.00/hr.
Most-aggressive quantisation we have a working recommendation for. Lower precision = less VRAM = cheaper hardware, at a small accuracy cost.
Cheapest hosted endpoints.
Variants in the Muse Spark family.
Meta: Muse Spark 1.3
Muse Spark 1.3 is a multimodal reasoning model from Meta for long-running age...
Meta: Muse Spark 1.2
Muse Spark 1.2 is a reasoning model from Meta, designed for complex agentic t...
Meta: Muse Spark 1.1
Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic t...
Meta: Muse Spark 1.3 Contributor
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s m...
Meta: Muse Spark 1.2 Contributor
Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for d...
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 refreshed hourly from each provider's API.
| Quantisation | Cheapest GPU config | Total VRAM | Live $/hr | tokens/sec | |
|---|---|---|---|---|---|
|
FP16
FP16 — half precision (default)
|
2160 GB | $53.84/hr | — | Compare → | |
|
FP8
FP8 — 8-bit float (Hopper / Blackwell)
|
1536 GB | $4.00/hr | — | Compare → | |
|
INT4
INT4 — 4-bit integer (~4× VRAM saving)
|
768 GB | $2.00/hr | — | Compare → |
What it costs per month across providers.
Estimate your monthly bill for Meta: Muse Spark Open 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.
Rent the GPU instead of paying per token.
For an open-weights model like Meta: Muse Spark Open, you can rent a GPU and serve inference yourself. The math: cheapest GPU rental × 730 hours/month + your electricity rate × power draw.
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.