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Inference.net vs Relace
Relace ships fast small models for coding-agent chores. Inference.net builds custom small models from your traffic and runs cheap batch.
By The Subconscious Team · Updated
Inference.net vs Relace: key differences
Relace and Inference.net share a thesis: specialized small models beat frontier LLMs on narrow tasks at lower cost. Relace applies it to coding agents with ready-made tools, like relace-apply-3 merging edits at about 10,000 tokens per second, parallel agentic search, and a compaction model at 50,000 tokens per second. Inference.net applies it to whatever task a customer runs, capturing gateway traffic, fine-tuning a task-specific model, and serving it on a dedicated GPU with a 99.99% uptime target. Relace ships the models; Inference.net helps you make one.
Relace is the faster start for coding workflows, since its models already exist and plug in through REST or OpenAI-compatible endpoints, with self-hosting for code kept in-house. Inference.net fits when the narrow task is yours alone, like a classification step once handled by a GPT-class model, or when bulk batch jobs dominate the bill. Relace errors past 128K tokens. Inference.net offers few independent benchmarks.
What Inference.net and Relace do
Inference.net
Inference.net started as a buyer of last resort for idle GPU time. Its scheduler aggregates small unused chunks of capacity across data centers and runs models on them, and it passes the steep discounts it gets from those data centers on to customers. That origin still shows in its OpenAI-compatible Batch API, which takes up to 1M requests per file with completion windows from 24 hours to 7 days and far higher headroom than synchronous limits.
Example models: open catalog models plus customer fine-tunes served on dedicated GPUs
Full Inference.net 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 Inference.net or Relace?
Inference.net
Choose Inference.net for
- Replacing a narrow GPT-class task with a distilled model
- Offline batch jobs at spare-capacity prices
- Routing and logging traffic across model vendors
Relace
Choose Relace for
- Ready-made apply and search models for coding agents
- Self-hosted coding tools for in-house code
- Fast context compaction in long agent runs
Inference.net vs Relace at a glance
| Attribute | Inference.net | Relace |
|---|---|---|
| Model access | Open, closed and custom | Specialist models |
| Flagship models | Customer fine-tunes | relace-apply-3, agentic search |
| Speed | Batch windows of 24h to 7 days | ~10,000 tok/s apply |
| Price | Discounted spare GPU capacity | 3x+ cheaper than full rewrites |
| Customization | Distill traces into custom models | Unknown |
| Deployment | Batch API, gateway, dedicated GPUs | Hosted API or self-hosted |
| Long context | Varies by model | 128K max |
Frequently asked questions
What is the difference between Inference.net and Relace?
Relace ships fast small models for coding-agent chores. Inference.net builds custom small models from your traffic and runs cheap batch.
When should I choose Inference.net over Relace?
Replacing a narrow GPT-class task with a distilled model; Offline batch jobs at spare-capacity prices; Routing and logging traffic across model vendors.
When should I choose Relace over Inference.net?
Ready-made apply and search models for coding agents; Self-hosted coding tools for in-house code; Fast context compaction in long agent runs.
Is Inference.net or Relace cheaper?
Inference.net: Discounted spare GPU capacity. Relace: 3x+ cheaper than full rewrites. The cheaper choice depends on the model and workload.
Which has more context, Inference.net or Relace?
Inference.net: Varies by model. 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.