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Cerebras vs Relace
Relace builds small tool models for coding agents: apply, search, compaction. Cerebras serves general open models at top speed. Complements, not rivals.
By The Subconscious Team · Updated
Cerebras vs Relace: key differences
Relace makes utility models for coding agents. Its relace-apply-3 merges a lazy edit into a file at about 10,000 tokens per second with 128K tokens of input and output, and its compaction model runs at 50,000 tokens per second. Relace argues that specialized small models beat frontier LLMs on these tasks while cutting cost. Cerebras is a general inference host, serving GPT-OSS 120B near 3,000 tokens per second on a wafer-scale chip. The two occupy different slots in an agent: Cerebras for generation, Relace for the mechanical steps around it.
Deployment options differ. Relace offers a hosted API, an OpenRouter listing and self-hosted deployment for enterprises that keep code in-house. Cerebras offers a shared API, dedicated endpoints and partners like OpenRouter, Hugging Face, Vercel and AWS Marketplace. Relace returns an error past 128K tokens, so very large files need a fallback model. Teams building PR review or CI tools can use Relace for search and apply, and route reasoning steps to a general host, Cerebras included when speed is the priority.
What Cerebras and Relace do
Cerebras
Cerebras builds a single chip the size of a silicon wafer, and its inference cloud is the fastest public host on the models it serves. Its developer table lists GPT-OSS 120B near 3,000 tokens per second, about six times Groq on the same weights, at $0.35 in and $0.75 out per million. The public shared catalog is thin, just GPT-OSS 120B and Qwen 3.8 27B since Gemma 4 31B moved to dedicated-only in September 2026. More model families live on dedicated endpoints and through partners like OpenRouter, Hugging Face, Vercel and AWS Marketplace.
Example models: GPT-OSS 120B, Qwen 3.8 27B
Full Cerebras profileRelace
Relace started out training small, fast models that act as tools for coding agents, and by October 2026 its homepage led with open-model inference instead. It says it served 30 trillion tokens in the 30 days to late October and ranks among the top providers on OpenRouter. The hosted catalog covers DeepSeek V4 Pro, V4 Flash and V4.1 Flash, Kimi K3, GLM 5.3, GLM 5.3 Flash and GLM 5.2 over OpenAI and Anthropic compatible APIs, billed per token with no subscription. Prices run from $0.07 in and $0.14 out per million tokens on DeepSeek V4 Flash to $2.00 in and $14.00 out on Kimi K3, and Relace says it reprices often.
Example models: DeepSeek V4.1 Flash, Kimi K3, GLM 5.3, relace-apply-3
Full Relace profileShould you choose Cerebras or Relace?
Cerebras
Choose Cerebras for
- Fast generation for a coding agent's reasoning steps
- Live autocomplete in an editor
- Access through AWS Marketplace or Vercel
Relace
Choose Relace for
- Instant apply of edits into user codebases
- Parallel agentic search across large repos
- Self-hosted coding utilities for code kept in-house
Cerebras vs Relace at a glance
| Attribute | Cerebras | Relace |
|---|---|---|
| Model access | Open weights | Open weights, plus specialist coding models |
| Flagship models | GPT-OSS 120B, Qwen 3.8 27B | DeepSeek V4.1 Flash, Kimi K3, GLM 5.3, relace-apply-3 |
| Speed | ~3,000 tok/s on GPT-OSS 120B | ~10,000 tok/s apply |
| Price | $0.35 in, $0.75 out (GPT-OSS 120B) | $0.07 in, $0.50 out (DeepSeek V4.1 Flash) |
| Customization | Unknown | Unknown |
| Deployment | Shared API, dedicated, partners | Hosted API, OpenRouter or self-hosted |
| Long context | 131K on GPT-OSS 120B, 128K on Qwen 3.8 27B | 128K on apply; varies by open model |
Frequently asked questions
What is the difference between Cerebras and Relace?
Relace builds small tool models for coding agents: apply, search, compaction. Cerebras serves general open models at top speed. Complements, not rivals.
When should I choose Cerebras over Relace?
Fast generation for a coding agent's reasoning steps; Live autocomplete in an editor; Access through AWS Marketplace or Vercel.
When should I choose Relace over Cerebras?
Instant apply of edits into user codebases; Parallel agentic search across large repos; Self-hosted coding utilities for code kept in-house.
Is Cerebras or Relace cheaper?
Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). Relace: $0.07 in, $0.50 out (DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, Cerebras or Relace?
Cerebras: 131K on GPT-OSS 120B, 128K on Qwen 3.8 27B. Relace: 128K on apply; varies by open model.
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.