Cohere Command A vs Nemotron (Nvidia)
Which one should you pick? Here's the full breakdown.
Cohere Command A
Cohere's enterprise-multilingual flagship -- 111B params, 256K context, runs on 2x H100. 23 languages. CC-BY-NC 4.0 on weights (research / non-commercial), commercial requires Cohere enterprise contract. Follow-ups: Command A Reasoning + Command A Vision
Nemotron (Nvidia)
Nvidia's open-weights family -- hybrid Mamba-Transformer MoE architecture, optimized for efficient reasoning on Nvidia hardware
| Category | Cohere Command A | Nemotron (Nvidia) |
|---|---|---|
| Ease of Use | 6.5 | 6.5 |
| Output Quality | 8.5 | 8.0 |
| Value | 7.0 | 8.0 |
| Features | 8.0 | 8.5 |
| Overall | 7.5 | 7.8 |
Pricing Comparison
| Feature | Cohere Command A | Nemotron (Nvidia) |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
Nemotron 3 Ultra (253B) benchmarks — Cohere Command A 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 Cohere Command A if...
Mid-size to large enterprises needing a multilingual open-weight model with low-ish infrastructure requirements (2x H100 for full model). Especially good for retrieval-augmented generation over internal document stores, multi-language customer support, and workflows touching Asian / Middle Eastern / African languages where Command A's coverage materially beats Llama or Mistral. Also a strong pick for teams already in Cohere's enterprise ecosystem.
Visit Cohere Command APick Nemotron (Nvidia) if...
- ✓Better value for money (8/10)
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
Cohere Command A and Nemotron (Nvidia) are extremely close overall. Your choice comes down to specific needs -- Cohere Command A is better for mid-size to large enterprises needing a multilingual open-weight model with low-ish infrastructure requirements (2x h100 for full model), while Nemotron (Nvidia) works best for teams running on nvidia hardware (tensorrt-llm, nim) who need efficient long-context reasoning.