Trinity Mini is $0.16 cheaper per 1M input tokens (77.5% lower; 4.44x difference).
API cost decision in 10 seconds
Trinity Mini vs INTELLECT-3
Pick Trinity Mini when budget is the priority.
Budget verdict
Pick Trinity Mini when budget is the priority.
On the standard 1M input plus 500K output workload, Trinity Mini is estimated at $0.12 vs $0.75 for INTELLECT-3, saving $0.63 (84% lower).
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $6.3. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Trinity Mini stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Trinity Mini | INTELLECT-3 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Trinity Mini | $0.3 | $1.55 |
| Balanced workload | 1M input + 1M output | Trinity Mini | $0.2 | $1.3 |
| Output-heavy chatbot | 1M input + 5M output | Trinity Mini | $0.8 | $5.7 |
Trinity Mini is $0.95 cheaper per 1M output tokens (86.4% lower; 7.33x difference).
Both models report the same context window at 131.07K tokens.
Trinity Mini is $0.63 cheaper on the standard workload (84% lower).
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 Mini has the lower input price; Trinity Mini has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Trinity Mini is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.12 for Trinity Mini and $0.75 for INTELLECT-3.
Choose Trinity Mini when you care most about lower input-token price, and lower output-token price.
Choose INTELLECT-3 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 Mini is estimated at $0.12 vs $0.75 for INTELLECT-3, saving $0.63 (84% lower).
- Trinity Mini is $0.63 cheaper on the standard workload (84% lower).
- Trinity Mini is $0.16 cheaper per 1M input tokens (77.5% lower; 4.44x difference).
- Trinity Mini is $0.95 cheaper per 1M output tokens (86.4% lower; 7.33x difference).
- Both models report the same context window at 131.07K tokens.
| Feature | Trinity Mini (Arcee AI) | INTELLECT-3 (Prime Intellect) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.045 | $0.2 |
| Completion Price per 1M tokens | $0.15 | $1.1 |
| Sample Workload Cost 1M input + 500K output | $0.12 | $0.75 |
| Context Window | 131.07K | 131.07K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Trinity Mini | On the standard 1M input plus 500K output workload, Trinity Mini is estimated at $0.12 vs $0.75 for INTELLECT-3, saving $0.63 (84% lower). |
| High-volume input processing | Trinity Mini | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Trinity Mini | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Trinity Large Thinking (free) can replace Trinity Mini when lower sample workload cost matters most: $0.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
Cheaper alternatives
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Open Prime Intellect modelsTrinity Mini is a 26B-parameter (3B active) sparse mixture-of-experts language model featuring 128 experts with 8 active per token. Engineered for efficient reasoning over long contexts (131k) with robust function...
INTELLECT-3 is a 106B-parameter Mixture-of-Experts model (12B active) post-trained from GLM-4.5-Air-Base using supervised fine-tuning (SFT) followed by large-scale reinforcement learning (RL). It offers state-of-the-art performance for its size across math,...