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Fireworks AI vs Relace
Relace makes small tool models for coding agents; Fireworks hosts the large open models those agents reason with. Most coding teams could run both.
By The Subconscious Team · Updated
Fireworks AI vs Relace: key differences
Relace is a toolkit, not a general host. Its relace-apply-3 model merges a frontier model's lazy edit snippet into the original file at about 10,000 tokens per second, which Relace says is over 3x faster and cheaper than a full rewrite. Its agentic search explores large repos in parallel, and a compaction model runs at 50,000 tokens per second. Fireworks is where an agent's main model can live: 400+ open models, full 1M context on DeepSeek V4 Pro, and a stack that posts 167 to 174 tokens per second on it in third-party tests.
The limits line up in a useful way. Relace returns an error past 128K tokens, so very large files need a fallback, and a long-context model on Fireworks can take that job. Relace offers self-hosted deployment for enterprises that keep code in-house, while Fireworks offers SOC 2, HIPAA and ISO on its hosted platform and fine-tuning of the main model with SFT, DPO or RL. App builders and PR-review pipelines can pair a Fireworks-hosted coder with Relace apply and search.
What Fireworks AI and Relace do
Fireworks AI
Fireworks AI was founded in 2022 by former Meta PyTorch engineers led by CEO Lin Qiao, and it sells speed on open models. Its custom serving stack has posted 167 to 174 tokens per second on DeepSeek V4 Pro in third-party measurements, several times what most GPU peers hit on the same model. The catalog holds 400+ models across text, vision, audio and embeddings, served through an OpenAI-compatible API. In July 2026 it raised a $1.505B Series D at a $17.5B valuation, with a reported $1B+ run rate and 40T+ tokens a day.
Example models: DeepSeek V4 Pro, Kimi K3
Full Fireworks AI profileRelace
Relace trains small, fast models that act as tools for coding agents. Its best-known product is Instant Apply: a frontier model writes a lazy edit snippet, and relace-apply-3 merges it into the original file at about 10,000 tokens per second with 128K tokens of input and output. Relace says this runs over 3x faster and cheaper than having the big model rewrite the file. It exposes both a REST endpoint and an OpenAI-compatible one, and the model is also listed on OpenRouter.
Example models: relace-apply-3, Relace agentic search
Full Relace profileShould you choose Fireworks AI or Relace?
Fireworks AI
Choose Fireworks AI for
- The main reasoning model for a coding agent
- Files and contexts well past 128K tokens
- Fine-tuning a coder with RL
Relace
Choose Relace for
- Instant apply of AI edits to user codebases
- Parallel search across large repos in PR review and CI
- Self-hosted coding utilities for code kept in-house
Fireworks AI vs Relace at a glance
| Attribute | Fireworks AI | Relace |
|---|---|---|
| Model access | Open weights | Specialist models |
| Flagship models | DeepSeek V4 Pro, Kimi K3 | relace-apply-3, agentic search |
| Speed | 167–174 tok/s on DeepSeek V4 Pro | ~10,000 tok/s apply |
| Price | Fine-tunes served at base price | 3x+ cheaper than full rewrites |
| Customization | SFT, DPO, RFT; Training API | Unknown |
| Deployment | Serverless, dedicated GPUs | Hosted API or self-hosted |
| Long context | Full 1M on DeepSeek V4 Pro | 128K max |
Frequently asked questions
What is the difference between Fireworks AI and Relace?
Relace makes small tool models for coding agents; Fireworks hosts the large open models those agents reason with. Most coding teams could run both.
When should I choose Fireworks AI over Relace?
The main reasoning model for a coding agent; Files and contexts well past 128K tokens; Fine-tuning a coder with RL.
When should I choose Relace over Fireworks AI?
Instant apply of AI edits to user codebases; Parallel search across large repos in PR review and CI; Self-hosted coding utilities for code kept in-house.
Is Fireworks AI or Relace cheaper?
Fireworks AI: Fine-tunes served at base price. Relace: 3x+ cheaper than full rewrites. The cheaper choice depends on the model and workload.
Which has more context, Fireworks AI or Relace?
Fireworks AI: Full 1M on DeepSeek V4 Pro. Relace: 128K max.
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.