Arcee Trinity-Large-Thinking vs Nemotron (Nvidia)
Which one should you pick? Here's the full breakdown.
Arcee Trinity-Large-Thinking
Arcee AI's US-made open-weight frontier reasoning model -- launched 2026-04-01. 398B total params, ~13B active. Sparse MoE (256 experts, 4 active = 1.56% routing). Apache 2.0, trained from scratch. #2 on PinchBench trailing only Claude 3.5 Opus. ~96% cheaper than Opus-4.6 on agentic tasks
Nemotron (Nvidia)
Nvidia's open-weights family -- hybrid Mamba-Transformer MoE architecture, optimized for efficient reasoning on Nvidia hardware
| Category | Arcee Trinity-Large-Thinking | Nemotron (Nvidia) |
|---|---|---|
| Ease of Use | 6.0 | 6.5 |
| Output Quality | 9.0 | 8.0 |
| Value | 9.5 | 8.0 |
| Features | 8.0 | 8.5 |
| Overall | 8.1 | 7.8 |
Pricing Comparison
| Feature | Arcee Trinity-Large-Thinking | Nemotron (Nvidia) |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
Nemotron 3 Ultra (253B) benchmarks — Arcee Trinity-Large-Thinking has no published benchmarks
| Benchmark | Description | Score |
|---|---|---|
| MMLU-Pro | Harder multi-subject reasoning | 79.8% |
| GPQA Diamond | Graduate-level science questions | 70.5% |
| AIME 2025 | 84.5% | |
| HumanEval | Python code generation | 89.6% |
| MMLU (Llama-Nemotron 70B) | 88.4% |
Which Should You Pick?
Pick Arcee Trinity-Large-Thinking if...
- ✓Higher output quality (9 vs 8)
- ✓Better value for money (9.5/10)
Teams that need a US-made, Apache 2.0, frontier-tier open-weight model and can either rent multi-GPU infrastructure or pay OpenRouter API pricing at ~$0.90/M output tokens. Particularly valuable for US government, defense, or regulated enterprise contexts where country-of-origin matters for procurement. Also good for agentic reasoning workloads where the ~96% cost savings vs Claude Opus actually changes what you can build.
Visit Arcee Trinity-Large-ThinkingPick Nemotron (Nvidia) if...
Teams running on Nvidia hardware (TensorRT-LLM, NIM) who need efficient long-context reasoning. Nemotron 3 Super is a standout for its 8 GB VRAM footprint with strong reasoning.
Visit Nemotron (Nvidia)Our Verdict
Arcee Trinity-Large-Thinking and Nemotron (Nvidia) are extremely close overall. Your choice comes down to specific needs -- Arcee Trinity-Large-Thinking is better for teams that need a us-made, apache 2, while Nemotron (Nvidia) works best for teams running on nvidia hardware (tensorrt-llm, nim) who need efficient long-context reasoning.