Trinity Large Thinking (free) is free for input tokens while Relace Search costs $1 per 1M tokens.
API cost decision in 10 seconds
Trinity Large Thinking (free) vs Relace Search
Pick Trinity Large Thinking (free) when budget and context both matter.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Trinity Large Thinking (free) when budget and context both matter.
On the standard 1M input plus 500K output workload, Trinity Large Thinking (free) is estimated at $0 vs $2.5 for Relace Search, saving $2.5 (100% lower).
Cost-first pickTrinity Large Thinking (free)
Context-first pickTrinity Large Thinking (free)
Sample savings$2.5100%
10x traffic gap$25
Trinity Large Thinking (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $25. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Trinity Large Thinking (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Trinity Large Thinking (free) | Relace Search |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Trinity Large Thinking (free) | $0 | $6.5 |
| Balanced workload | 1M input + 1M output | Trinity Large Thinking (free) | $0 | $4 |
| Output-heavy chatbot | 1M input + 5M output | Trinity Large Thinking (free) | $0 | $16 |
Trinity Large Thinking (free) is free for output tokens while Relace Search costs $3 per 1M tokens.
Trinity Large Thinking (free) has 6.14K more context (1.02x larger).
Trinity Large Thinking (free) is free for the standard workload while the other model is estimated at $2.5.
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
Trinity Large Thinking (free) has the lower input price; Trinity Large Thinking (free) has the lower output price; Trinity Large Thinking (free) offers the larger context window. For the 1M input plus 500K output sample, Trinity Large Thinking (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Trinity Large Thinking (free) and $2.5 for Relace Search.
Choose Trinity Large Thinking (free) when you care most about lower input-token price, lower output-token price, and larger context window.
Choose Relace Search when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
- On the standard 1M input plus 500K output workload, Trinity Large Thinking (free) is estimated at $0 vs $2.5 for Relace Search, saving $2.5 (100% lower).
- Trinity Large Thinking (free) is free for the standard workload while the other model is estimated at $2.5.
- Trinity Large Thinking (free) is free for input tokens while Relace Search costs $1 per 1M tokens.
- Trinity Large Thinking (free) is free for output tokens while Relace Search costs $3 per 1M tokens.
- Trinity Large Thinking (free) has 6.14K more context (1.02x larger).
| Feature | Trinity Large Thinking (free) (Arcee AI) | Relace Search (Relace) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $1 |
| Completion Price per 1M tokens | $0 | $3 |
| Sample Workload Cost 1M input + 500K output | $0 | $2.5 |
| Context Window | 262.14K | 256K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Trinity Large Thinking (free) | On the standard 1M input plus 500K output workload, Trinity Large Thinking (free) is estimated at $0 vs $2.5 for Relace Search, saving $2.5 (100% lower). |
| High-volume input processing | Trinity Large Thinking (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Trinity Large Thinking (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Trinity Large Thinking (free) | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Relace Apply 3 can replace Relace Search when lower sample workload cost matters most: $1.48.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- Gemini 3.1 Flash Lite offers 1.05M context with $1 sample workload cost.
- No popular competitor is currently available.
Cheaper alternatives
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Open Relace modelsTrinity Large Thinking is a powerful open source reasoning model from the team at Arcee AI. It shows strong performance in PinchBench, agentic workloads, and reasoning tasks. Launch video: https://youtu.be/Gc82AXLa0Rg?si=4RLn6WBz33qT--B7...
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...