Morph vs Relace
A side-by-side comparison of Morph and Relace, two Inference tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Morph | Relace |
|---|---|---|
| Category | Inference | Inference |
| Pricing | FREEMIUM | FREEMIUM |
| License | Proprietary | Proprietary |
| Deployment (differs) | Cloud | Hybrid |
| Platforms (differs) | API, Web | Web, API |
| Model support (differs) | Multi-model | Self-contained (on-device) |
| Vendor (differs) | Morph | Relace |
| Capabilities (differs) |
|
|
The honest brief
Morph
A dedicated Fast Apply model that merges LLM code edits at ~10,500 tok/s — purpose-built write layer for agents.
- Merges edits without full-file rewrites
- OpenAI-compatible API
- Used in production by JetBrains, Vercel
- Adds code search and context compaction
- Narrow, infra-layer use case
- Closed source
- Most useful only inside coding agents
Relace
An 'Instant Apply' model merges LLM diffs into full files at thousands of tokens/sec — faster and cheaper than a frontier model rewriting whole files.
- Two-stage code retrieval + reranker
- Managed repo hosting, auto-indexed per commit
- Drops into existing codegen stacks
- Powers Lovable, Create, Magic Patterns
- Self-host / VPC option for enterprise
- No public pricing detail
- Narrow focus: codegen infra only
- Newer and smaller than general LLM APIs
When to pick which
Both cover Code generation and Model inference / serving.
Pick Morph if you need LLM gateway / routing.
- LLM gateway / routing (primary capability)
Pick Relace if you need Vector search and Embeddings.
- Vector search (secondary capability)
- Embeddings (secondary capability)
Relace leans on Code generation as a headline capability; Morph treats it as secondary.
- Code generation (primary capability)
They also differ on:
- Deployment
- Cloud · Hybrid
- Model support
- Multi-model · Self-contained (on-device)