Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Nova 2.0 Pro Preview (Non-reasoning) | Gemini 2.5 Pro |
|---|---|---|
| Input ($/M tokens) | $1.25 | $1.25 |
| Output ($/M tokens) | $10 | $10 |
Verdict. Gemini 2.5 Pro 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 mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Gemini 2.5 Pro is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Gemini 2.5 Pro makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Nova 2.0 Pro Preview (Non-reasoning) is strongest on Coding Index (20.9), Intelligence Index (14.4). Gemini 2.5 Pro leads on Coding Index (33.3), Intelligence Index (25.9).
Speed. On throughput, Gemini 2.5 Pro generates tokens at 133 tok/s versus 104 tok/s — about 22% faster. On time-to-first-token, Nova 2.0 Pro Preview (Non-reasoning) responds in 1040ms vs 20460ms, which matters most for chat-style UIs.
Provider. Amazon and Google sell to overlapping but distinct developer audiences: Amazon tends to ship frontier reasoning models with premium positioning, while Google 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): Nova 2.0 Pro Preview (Non-reasoning) costs $187.50 ($2250/year); Gemini 2.5 Pro costs $187.50 ($2250/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Nova 2.0 Pro Preview (Non-reasoning) ≈ $26.25/run, Gemini 2.5 Pro ≈ $26.25/run. At agent/realtime scale (200M input / 100M output per million requests): Nova 2.0 Pro Preview (Non-reasoning) ≈ $1250/run, Gemini 2.5 Pro ≈ $1250/run.
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.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
Gemini 2.5 Pro wins 2 out of 12 benchmarks compared to 0 for Nova 2.0 Pro Preview (Non-reasoning). See the detailed benchmark chart above for per-category results.
Gemini 2.5 Pro generates tokens faster at 133 tok/s vs 104 tok/s. Nova 2.0 Pro Preview (Non-reasoning) also has lower time-to-first-token (1.04s vs 20.46s).
Choose based on your priorities: both are similarly priced, Gemini 2.5 Pro for stronger benchmark performance, and Gemini 2.5 Pro for faster generation. For latency-sensitive apps, check the TTFT comparison above.