Relace Search API256K context
The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request.
Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).
What is Relace Search?
The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request. In contrast to RAG, relace-search performs agentic...
Relace Search pricing
Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):
| Model | Input / 1M | Output / 1M | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| Relace Search | $1.00 | $3.00 | — | — | 256K |
On output price, Relace Search is cheaper than 34% of the 309 models in the catalog.
What Relace Search costs per month
| Workload | Tokens in / out (monthly) | Est. cost |
|---|---|---|
| Support chatbot | 40M / 12M | $76.00 |
| RAG / knowledge base | 200M / 20M | $260 |
| Coding agent | 80M / 25M | $155 |
| Batch extraction | 150M / 8M | $174 |
| Content generation | 20M / 40M | $140 |
Estimate your own monthly cost
Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.
Relace Search vs alternatives
| Model | Input / 1M | Output / 1M | Context | Our test |
|---|---|---|---|---|
| Relace Search | $1.00 | $3.00 | 256K | — |
| Relace Apply 3 | $0.85 | $1.25 | 256K | — |
| Gemini 3 Flash Preview | $0.50 | $3.00 | 1M | — |
| Nano Banana 2 (Gemini 3.1 Flash Image Preview) | $0.50 | $3.00 | 131K | — |
| Hermes 4 405B | $1.00 | $3.00 | 131K | — |
When not to use Relace Search
- It is served by a single provider, so there is less failover headroom during an outage.
Specs
| Model ID | relace/relace-search |
| Modality | text->text (input: text) |
| Context window | 256,000 tokens |
| Max output | 128,000 tokens |
| Tool / function calling | ✅ Yes |
| Structured output (JSON) | ✅ Yes |
| Released | 2025-12-08 |
| Open weights | — (hosted API only) |
How to call Relace Search
from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
model="relace/relace-search",
messages=[{"role": "user", "content": "Hello"}],
# supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)curl https://api.datallmlab.com/v1/chat/completions \
-H "Authorization: Bearer YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"relace/relace-search","messages":[{"role":"user","content":"Hello"}]}'import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
model: "relace/relace-search",
messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);The same key routes Relace Search and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.
Prompting tips for Relace Search
- Be explicit and show the shape of the answer. Spell out format, tone and constraints up front, and include one short example of the output you want — Relace Search follows concrete instructions better than abstract ones.
- Huge 256K context — but anchor the ask. You can paste whole documents or codebases; models attend most to the start and end, so put the key instruction at the top and restate it after long inputs.
- Give it real tools. Pass a
tools=[...]schema instead of asking it to "pretend" — let Relace Search emit tool calls, execute them, and feed results back for the next turn. - Constrain JSON with a schema. Use
response_format/ structured outputs rather than "reply in JSON" to get valid, parseable objects every time.
Tips are derived from Relace Search's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.
Open-source tools for Relace Search
Popular open-source frameworks and agents to build with Relace Search over the API — star counts pulled from GitHub (July 2026).
Listed by GitHub stars; inclusion is by ecosystem relevance (agent frameworks, SDKs and gateways), not affiliation. Stars change — see each repo for current numbers.
Migrating to Relace Search
Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → relace/relace-search. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.
Rate limits & reliability
Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.
Related reading
Call Relace Search with one key
300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.
Get an API keyCompare pricingFrequently asked questions
What is Relace Search?
The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request. It accepts text input with a 256K-token context window and was released on 2025-12-08. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.
How much does Relace Search cost?
On DataLLM Lab it is $1.00 per 1M input tokens and $3.00 per 1M output tokens — cheaper than about 34% of the 309-model catalog on output price. Pay-as-you-go, no subscription.
What is the context window of Relace Search?
256K tokens, with up to 128K max output tokens.
Is Relace Search open source?
No open weights are published — it is available through hosted API access only.
How do I call the Relace Search API?
Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "relace/relace-search". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.
What are good alternatives to Relace Search?
Close options by price and capability include Relace Apply 3, Gemini 3 Flash Preview, Nano Banana 2 (Gemini 3.1 Flash Image Preview) — all callable with the same DataLLM Lab key.