Intelligence
N/A
44
General reasoning and benchmark headroom.
SituationalRelace: Relace Search is a budget text-first model from relace with a heavy runtime profile, large context posture, and the clearest fit around long-context research / reasoning.
Benchmark blend
Dev workflow signal
Large
Budget tier
Relace: Relace Search currently reads as a budget text-first option with large context and a heavy runtime profile.
Decision Strip
Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.
General reasoning and benchmark headroom.
SituationalLatency data is partial.
SituationalHow much prompt and task state can stay in view.
Above average$3.00 output / 1M
EfficientEditorial Profile
Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.
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 multi-step reasoning to produce highly precise results 4x faster than any frontier model. It's designed to serve as a subagent that passes its findings to an "oracle" coding agent, who orchestrates/performs the rest of the coding task. To use relace-search you need to build an appropriate agent harness, and parse the response for relevant information to hand off to the oracle. Read more about it in the [Relace documentation](https://docs.relace.ai/docs/fast-agentic-search/agent).
relace text-first profile
Long-context research / Reasoning with large context and heavy runtime.
Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.
Large context headroom supports repo-wide prompts and long research sessions.
Budget-friendly input pricing is a strength, but raw capability may vary by workload.
Latency profile is better for deliberate runs than rapid back-and-forth chat.
Current metadata points to a text-first profile rather than a broad multimodal one.
Long-context summarization, repo analysis, and policy or document review.
Benchmarks
Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.
Specs & Pricing
Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.
This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.
Metadata
Verification details remain available, but the page no longer forces them ahead of the editorial read.