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Modal vs Morph
Morph merges coding-agent edits at 10,500+ tokens per second. Modal is a GPU and sandbox platform that coding pipelines often run on. Morph even lists Modal as a place its apply model gets used.
By The Subconscious Team · Updated
Modal vs Morph: key differences
These are complements. Morph sells a specialist 7B model that merges a frontier model's edit snippets into full files at 10,500+ tokens per second with up to 98% accuracy, plus WarpGrep for repo search, Compact for context and Reflex for classification. Modal sells serverless GPU compute and agent sandboxes for Python, billed per second. Morph's own use cases include CI pipelines and sandboxes like E2B, Modal or Daytona that edit code at volume. Neither sells what the other does, and each makes the other more useful.
A typical split puts the agent's execution environment on Modal, where it clones repos, runs tests and hosts any custom models, and calls Morph's API for the apply step. Morph says this cuts about 40% of tokens against full-file rewrites. Its 2 to 4% merge error rate is one reason the tests running in the sandbox matter. Modal could host an apply-style model too, but that means building and serving one. Morph is a narrow tool and does not replace a general host.
What Modal and Morph 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 profileMorph
Morph builds small, very fast specialist models that sit beside a big coding model inside an agent. Its flagship is Fast Apply. The frontier model writes only the changed lines with // ... existing code ... markers, and Morph merges them into the full file at 10,500+ tokens per second with up to 98% accuracy. It is the same idea behind Cursor's instant apply, offered as an OpenAI-compatible API.
Example models: morph-v3-fast, morph-v3-large
Full Morph profileShould you choose Modal or Morph?
Modal vs Morph at a glance
| Attribute | Modal | Morph |
|---|---|---|
| Model access | Bring your own weights | Specialist models |
| Flagship models | None hosted | morph-v3-fast, morph-v3-large |
| Speed | ~1s container boot | 10,500+ tok/s Fast Apply |
| Price | Per second; H100 $3.95/hr list | ~40% fewer tokens than full rewrites |
| Customization | Run any training code | Fine-tuning offered |
| Deployment | Serverless GPU containers | OpenAI-compatible API |
| Long context | Depends on the model you deploy | Unknown |
Frequently asked questions
What is the difference between Modal and Morph?
Morph merges coding-agent edits at 10,500+ tokens per second. Modal is a GPU and sandbox platform that coding pipelines often run on. Morph even lists Modal as a place its apply model gets used.
When should I choose Modal over Morph?
Sandboxes where coding agents run tests; Hosting custom models beside the agent; Batch code jobs billed by the second.
When should I choose Morph over Modal?
Fast, accurate merges of model edits into files; Cutting frontier-model output tokens; Repo search and context compression as API calls.
Is Modal or Morph cheaper?
Modal: Per second; H100 $3.95/hr list. Morph: ~40% fewer tokens than full rewrites. The cheaper choice depends on the model and workload.
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.