Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) | GPT-4o mini |
|---|---|---|
| Input ($/M tokens) | $0.2 | $0.15 |
| Output ($/M tokens) | $0.6 | $0.6 |
Verdict. GPT-4o mini takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, GPT-4o mini is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-4o mini makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) is strongest on Intelligence Index (5.8). GPT-4o mini leads on Coding Index (11.4), Intelligence Index (6.7).
Speed. On throughput, NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) generates tokens at 198 tok/s versus 154 tok/s — about 22% faster. On time-to-first-token, GPT-4o mini responds in 870ms vs 1160ms, which matters most for chat-style UIs.
Provider. NVIDIA and OpenAI sell to overlapping but distinct developer audiences: NVIDIA tends to ship frontier reasoning models with premium positioning, while OpenAI often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) costs $15.00 ($180/year); GPT-4o mini costs $13.50 ($162/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) ≈ $2.20/run, GPT-4o mini ≈ $1.95/run. At agent/realtime scale (200M input / 100M output per million requests): NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) ≈ $100/run, GPT-4o mini ≈ $90/run. GPT-4o mini becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Data from Artificial Analysis API — 12 benchmarks
GPT-4o mini is cheaper overall. Its blended price (3:1 input/output ratio) is $0.26/M tokens vs $0.30/M for NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning).
GPT-4o mini wins 2 out of 12 benchmarks compared to 0 for NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning). See the detailed benchmark chart above for per-category results.
NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) generates tokens faster at 198 tok/s vs 154 tok/s. However, GPT-4o mini has lower time-to-first-token (0.87s vs 1.16s).
Choose based on your priorities: GPT-4o mini for lower cost, GPT-4o mini for stronger benchmark performance, and NVIDIA Nemotron Nano 12B v2 VL (Non-reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.