Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | NVIDIA Nemotron Nano 9B V2 (Reasoning) | Sarvam 105B (high) |
|---|---|---|
| Input ($/M tokens) | $0.04 | $0.04 |
| Output ($/M tokens) | $0.16 | $0.17 |
Verdict. Sarvam 105B (high) takes the aggregate benchmark matchup 1–0 across 1 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 0.9× the per-million-token cost, NVIDIA Nemotron Nano 9B V2 (Reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). NVIDIA Nemotron Nano 9B V2 (Reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. NVIDIA Nemotron Nano 9B V2 (Reasoning) is strongest on Intelligence Index (8.7). Sarvam 105B (high) leads on Intelligence Index (11.9).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. NVIDIA and Sarvam sell to overlapping but distinct developer audiences: NVIDIA tends to ship frontier reasoning models with premium positioning, while Sarvam 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 9B V2 (Reasoning) costs $3.60 ($43/year); Sarvam 105B (high) costs $3.75 ($45/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): NVIDIA Nemotron Nano 9B V2 (Reasoning) ≈ $0.52/run, Sarvam 105B (high) ≈ $0.54/run. At agent/realtime scale (200M input / 100M output per million requests): NVIDIA Nemotron Nano 9B V2 (Reasoning) ≈ $24/run, Sarvam 105B (high) ≈ $25/run. NVIDIA Nemotron Nano 9B V2 (Reasoning) 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
NVIDIA Nemotron Nano 9B V2 (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.07/M tokens vs $0.07/M for Sarvam 105B (high).
Sarvam 105B (high) wins 1 out of 12 benchmarks compared to 0 for NVIDIA Nemotron Nano 9B V2 (Reasoning). See the detailed benchmark chart above for per-category results.
NVIDIA Nemotron Nano 9B V2 (Reasoning) generates tokens faster at 186 tok/s vs — tok/s. NVIDIA Nemotron Nano 9B V2 (Reasoning) also has lower time-to-first-token (4.08s vs —s).
Choose based on your priorities: NVIDIA Nemotron Nano 9B V2 (Reasoning) for lower cost, Sarvam 105B (high) for stronger benchmark performance, and NVIDIA Nemotron Nano 9B V2 (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.