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Modal vs OpenScale
Modal rents GPUs by the second for models you deploy yourself. OpenScale sells one open model per token with nothing to deploy.
By The Subconscious Team · Updated
Modal vs OpenScale: key differences
Modal runs any Python workload on GPUs from T4 to B300, with per-second billing, about one second of container boot and $30 of free credits each month. Teams bring their own weights and serving code. OpenScale, a Y Combinator-backed API out of Singapore, serves DeepSeek V4.1 Flash with a 1M context at $0.06 in, $0.003 cached and $0.24 out per million tokens under a 50% promotion, at 200+ tokens per second.
Modal fits custom models, fine-tunes, embeddings and batch jobs where control over the stack matters. OpenScale fits teams that just want cheap DeepSeek tokens behind an OpenAI or Anthropic-compatible endpoint, with tested setups for Claude Code, Codex and other coding agents. Hosting DeepSeek V4.1 Flash on Modal is possible but means paying for GPUs and keeping them warm.
What Modal and OpenScale 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 profileOpenScale
OpenScale is a Y Combinator-backed inference API built by LatentSpace and run out of Singapore. It sells open models behind one endpoint that speaks Chat Completions, the OpenAI Responses API and Anthropic Messages, so Claude Code, Codex, OpenCode, Cline, GitHub Copilot, Zed and other coding agents can point at it with a base URL and key. Its public catalog today is DeepSeek V4.1 Flash in two versions, standard and fast, both with a 1M token context window and up to 384K output tokens.
Example models: DeepSeek V4.1 Flash
Full OpenScale profileShould you choose Modal or OpenScale?
Modal vs OpenScale at a glance
| Attribute | Modal | OpenScale |
|---|---|---|
| Model access | Bring your own weights | Open weights |
| Flagship models | None hosted | DeepSeek V4.1 Flash |
| Speed | ~1s container boot | 200+ tok/s; fast tier ~2x |
| Price | Per second; H100 $3.95/hr list | $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash) |
| Customization | Run any training code | N/A |
| Deployment | Serverless GPU containers | Serverless API |
| Long context | Depends on the model you deploy | 1M context |
Frequently asked questions
What is the difference between Modal and OpenScale?
Modal rents GPUs by the second for models you deploy yourself. OpenScale sells one open model per token with nothing to deploy.
When should I choose Modal over OpenScale?
Serving your own or fine-tuned models; Per-second GPU billing; Batch, embedding and media jobs.
When should I choose OpenScale over Modal?
Cheap DeepSeek V4.1 Flash with nothing to deploy; Coding agent backends; Prepaid credits with no minimums.
Is Modal or OpenScale cheaper?
Modal: Per second; H100 $3.95/hr list. OpenScale: $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, Modal or OpenScale?
Modal: Depends on the model you deploy. OpenScale: 1M context.
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.