vs

Modal vs Meta

Meta sells Muse Spark through a preview API and ships open Muse Glimmer for self-hosting. Modal rents per-second GPUs to run models like Glimmer yourself. API versus runtime.

By The Subconscious Team · Updated

Modal vs Meta: key differences

Meta now runs a closed API. Muse Spark 1.3 offers a 1M context at $1.25 in and $4.25 out per million, with cached input at $0.15, and the endpoint speaks OpenAI, Anthropic and a stateful agentic format. A Contributor tier drops the price to $0.10 in and $0.20 out if Meta can train on your traffic. For self-hosting, Meta ships Muse Glimmer, an open-weight model distilled from Muse Spark that runs on vLLM, SGLang, llama.cpp or ExecuTorch. Meta hosts the model; Modal hosts only what you deploy.

Modal is where Glimmer, or any other open model, could run. It builds the container, scales it to zero and bills per second, which beats reserved GPUs on bursty load below roughly 80% utilization. That route suits teams that cannot hand data to Meta or want to customize the model. The Meta API suits teams that want Muse Spark's agentic and computer-use abilities, plus Muse Image at $0.01 per image, without running anything. Note the API is still in public preview.

What Modal and Meta do

Modal

Modal is serverless compute with GPUs attached. A developer decorates a Python function with the hardware it needs, such as gpu="H100", and Modal builds the container, schedules it, autoscales it and scales it back to zero. Billing runs per second with no minimum increment, from $0.59 an hour for a T4 to $3.95 for an H100 at list. Containers can hold up to 8 GPUs across T4 through B300.

Example models: none hosted by default; teams deploy their own, such as open LLMs on vLLM or Whisper

Full Modal profile

Meta

Meta has moved from open Llama releases toward its own closed API. Meta Superintelligence Labs builds the Muse family, and in July 2026 Meta opened a public preview of the Meta Model API with Muse Spark 1.1, a multimodal reasoning model aimed at agentic coding, tool use and computer use. The current lineup runs through Muse Spark 1.3 with a 1M token context. Standard pricing is $1.25 in and $4.25 out per million tokens, with cached input at $0.15, and the endpoint speaks OpenAI Chat Completions, Anthropic Messages and a stateful agentic format.

Example models: Muse Spark 1.3, Muse Glimmer

Full Meta profile

Should you choose Modal or Meta?

Modal

Choose Modal for

  • Self-hosting Muse Glimmer or other open models.
  • Workloads where no data can go to a model vendor.
  • Bursty GPU use billed by the second.

Meta

Choose Meta for

  • Muse Spark for agentic coding and computer use.
  • Near-free prototyping on the Contributor tier.
  • Cheap image generation and transcription on one key.

Modal vs Meta at a glance

AttributeModalMeta
Model accessBring your own weightsClosed API; open Muse Glimmer
Flagship modelsNone hostedMuse Spark 1.3, Muse Glimmer
Speed~1s container boot~145–233 tok/s on Muse Spark 1.3
PricePer second; H100 $3.95/hr list$1.25 in, $4.25 out; Contributor tier cheaper
CustomizationRun any training codeOpen Muse Glimmer weights to fine-tune
DeploymentServerless GPU containersMeta Model API (preview)
Long contextDepends on the model you deploy1M

Frequently asked questions

What is the difference between Modal and Meta?

Meta sells Muse Spark through a preview API and ships open Muse Glimmer for self-hosting. Modal rents per-second GPUs to run models like Glimmer yourself. API versus runtime.

When should I choose Modal over Meta?

Self-hosting Muse Glimmer or other open models; Workloads where no data can go to a model vendor; Bursty GPU use billed by the second.

When should I choose Meta over Modal?

Muse Spark for agentic coding and computer use; Near-free prototyping on the Contributor tier; Cheap image generation and transcription on one key.

Is Modal or Meta cheaper?

Modal: Per second; H100 $3.95/hr list. Meta: $1.25 in, $4.25 out; Contributor tier cheaper. The cheaper choice depends on the model and workload.

Which has more context, Modal or Meta?

Modal: Depends on the model you deploy. Meta: 1M.

Related comparisons

Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.