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Sail Research vs Relace
Sail Research runs the reasoning model cheaply by making it wait. Relace runs the utility steps (apply, search, compaction) as fast as it can. They split one coding agent's work.
By The Subconscious Team · Updated
Sail Research vs Relace: key differences
Relace trains small models that act as tools inside coding agents. relace-apply-3 merges lazy edit snippets at about 10,000 tokens per second, its agentic search explores large codebases in seconds, and a compaction model runs at 50,000 tokens per second. Sail Research hosts the general open models an agent thinks with, such as Kimi K2.6, GLM-5.3, GPT-OSS 120B and Qwen 3.6, and prices them by patience. Against traditional providers, the default low-latency asap window costs 30 to 70% less and the balanced window 45 to 80% less.
Neither replaces the other. Relace hosts only a handful of open models, and Sail has no specialist apply or search models. A PR review or automated-fix pipeline could run its planner on Sail's balanced window and call Relace for retrieval and merges, keeping expensive tokens off the main model. Limits differ: Relace returns an error past 128K tokens, so very large files need a fallback, while Sail's custom-tool requests default to the slower balanced window. Relace also offers self-hosted deployment for teams that keep code in-house.
What Sail Research and Relace do
Sail Research
Sail Research sells throughput over latency. Founders Neil Movva and Samir Menon built a serving stack that packs as much work as possible into every GPU, and customers state how long they can wait through completion windows. Its docs quote each window against traditional providers: the default asap window serves at low latency for 30 to 70% less, balanced for 45 to 80% less, and the off-peak flex window for 55 to 85% less. Batch requests default to flex, and LoRA and custom-tool requests default to balanced.
Example models: Kimi K2.6, GLM-5.3
Full Sail Research 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 Sail Research or Relace?
Sail Research
Choose Sail Research for
- The main reasoning model for unattended coding agents.
- Cheap open-model tokens when turns can take minutes.
- Customer LoRA fine-tunes served over OpenAI or Anthropic APIs.
Relace
Choose Relace for
- Fast file merges and repo search inside an agent loop.
- Context compaction at 50,000 tokens per second.
- Self-hosted coding utilities for code that stays in-house.
Sail Research vs Relace at a glance
| Attribute | Sail Research | Relace |
|---|---|---|
| Model access | Open weights | Open weights, plus specialist coding models |
| Flagship models | Kimi K2.6, GLM-5.3, GPT-OSS 120B | DeepSeek V4.1 Flash, Kimi K3, GLM 5.3, relace-apply-3 |
| Speed | Low-latency default; slower windows cheaper | ~10,000 tok/s apply |
| Price | 30–85% below other hosts by completion window | $0.07 in, $0.50 out (DeepSeek V4.1 Flash) |
| Customization | Customer LoRA fine-tunes | Unknown |
| Deployment | API plus Sailboxes | Hosted API, OpenRouter or self-hosted |
| Long context | Varies by model | 128K on apply; varies by open model |
Frequently asked questions
What is the difference between Sail Research and Relace?
Sail Research runs the reasoning model cheaply by making it wait. Relace runs the utility steps (apply, search, compaction) as fast as it can. They split one coding agent's work.
When should I choose Sail Research over Relace?
The main reasoning model for unattended coding agents; Cheap open-model tokens when turns can take minutes; Customer LoRA fine-tunes served over OpenAI or Anthropic APIs.
When should I choose Relace over Sail Research?
Fast file merges and repo search inside an agent loop; Context compaction at 50,000 tokens per second; Self-hosted coding utilities for code that stays in-house.
Is Sail Research or Relace cheaper?
Sail Research: 30–85% below other hosts by completion window. Relace: $0.07 in, $0.50 out (DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, Sail Research or Relace?
Sail Research: Varies by model. 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.