Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Nemotron 3 Nano Omni 30B A3B Reasoning | GLM-4.7-Flash (Reasoning) |
|---|---|---|
| Input ($/M tokens) | $0.09 | $0.07 |
| Output ($/M tokens) | $0.36 | $0.4 |
Verdict. Nemotron 3 Nano Omni 30B A3B Reasoning and GLM-4.7-Flash (Reasoning) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Both models sit in the budget bracket for output-token pricing. At 0.9× the per-million-token cost, Nemotron 3 Nano Omni 30B A3B Reasoning is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Nemotron 3 Nano Omni 30B A3B Reasoning makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Nemotron 3 Nano Omni 30B A3B Reasoning is strongest on Coding Index (13.8), Intelligence Index (10.3). GLM-4.7-Flash (Reasoning) leads on Intelligence Index (14.9).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. NVIDIA and Z AI sell to overlapping but distinct developer audiences: NVIDIA tends to ship frontier reasoning models with premium positioning, while Z AI 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): Nemotron 3 Nano Omni 30B A3B Reasoning costs $8.10 ($97/year); GLM-4.7-Flash (Reasoning) costs $8.10 ($97/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Nemotron 3 Nano Omni 30B A3B Reasoning ≈ $1.17/run, GLM-4.7-Flash (Reasoning) ≈ $1.15/run. At agent/realtime scale (200M input / 100M output per million requests): Nemotron 3 Nano Omni 30B A3B Reasoning ≈ $54/run, GLM-4.7-Flash (Reasoning) ≈ $54/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
GLM-4.7-Flash (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.15/M tokens vs $0.16/M for Nemotron 3 Nano Omni 30B A3B Reasoning.
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
GLM-4.7-Flash (Reasoning) generates tokens faster at 77 tok/s vs — tok/s. However, GLM-4.7-Flash (Reasoning) has lower time-to-first-token (1.58s vs —s).
Choose based on your priorities: GLM-4.7-Flash (Reasoning) for lower cost, both perform similarly on benchmarks, and GLM-4.7-Flash (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.