Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Nemotron 3 Nano Omni 30B A3B Reasoning by NVIDIA and Nemotron 3 Super 120B A12B by NVIDIA represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Nemotron 3 Nano Omni 30B A3B Reasoning holds a notable pricing advantage for token ingestion. On output generation, Nemotron 3 Nano Omni 30B A3B Reasoning is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Nemotron 3 Super 120B A12B provides an expanded memory horizon with 262K tokens. In latency-sensitive production environments, Nemotron 3 Nano Omni 30B A3B Reasoning leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Nemotron 3 Nano Omni 30B A3B Reasoning
Omni MoEUnified omnimodal MoE combining text, high-resolution vision, and direct audio ingestion with step-by-step reasoning.
$0.20 / 1M
$0.60 / 1M
256K tokens
42%
Nemotron 3 Super 120B A12B
Collaborative AgentCollaborative agent workhorse activating 12B out of 120B parameters, delivering flagship-grade reasoning at high batch throughput.
$0.30 / 1M
$0.80 / 1M
262.1K tokens
51%
Key Differences at a Glance
- Nemotron 3 Nano Omni 30B A3B Reasoning is 1.4x cheaper for API usage (input + output tokens combined).
- Nemotron 3 Super 120B A12B has a larger context window (262K vs 256K tokens).
- Nemotron 3 Nano Omni 30B A3B Reasoning is faster at 105 tok/s vs 85 tok/s.
- Nemotron 3 Super 120B A12B leads on SWE-bench coding (51.0% vs 42.0%).
| Feature | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 48 | 53 |
Provider | NVIDIA | NVIDIA |
Input Price Cost per million input tokens | $0.20 / 1M | $0.30 / 1M |
Output Price Cost per million output tokens | $0.60 / 1M | $0.80 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.14 / 1M | $0.18 / 1M |
Context Window Maximum input + output tokens | 256K tokens~384 A4 pages of text | 262.1K tokens~393 A4 pages of text |
Max Output Tokens Per single request | 16K | 33K |
Throughput Speed Tokens generated per second | 105 tok/s | 85 tok/s |
SWE-bench Verified Real-world software engineering | 42% | 51% |
GPQA Diamond Graduate-level reasoning | 56.5% | 64.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.05 / 1M | $0.06 / 1M |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Nemotron 3 Nano Omni 30B A3B Reasoning · Strengths & Key Advantages
- Native tri-modal comprehension across text, high-res vision, and audio streams
- 3B active parameter inference speed with 256K token context window
- Open weights deployable on edge robotics and local workstation rigs
Considerations & Trade-offs
- Speech generation is text-only (requires external TTS for voice responses)
- Trails specialized 100B+ models on competitive coding
Nemotron 3 Super 120B A12B · Strengths & Key Advantages
- 12B active parameter inference speed paired with 120B total capacity knowledge
- Outstanding 262K context handling with zero needle-in-a-haystack dropoff
- Engineered specifically for autonomous multi-agent swarm coordination
Considerations & Trade-offs
- Requires dual 80GB enterprise GPUs for local deployment
- Text-only without native multimodal image inputs
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $0.38 |
Output Tokens / Task Tokens generated per task | 28K | 38K |
Reasoning Tokens / Task Thinking tokens burned per task | 12K | 18K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | Nemotron 3 Nano Omni 30B A3B Reasoning | Nemotron 3 Super 120B A12B |
|---|---|---|
| Official API Model ID (SDK) | nemotron-3-nano-omni-30b-a3b | nemotron-3-super-120b-a12b |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-04 | 2026-03 |
| Knowledge Cutoff | February 2026 | January 2026 |
| Architecture | Omnimodal Sparse MoE (30B Total / 3B Active) | High-Throughput Sparse MoE (120B Total / 12B Active) |
| Parameters | 30B (3B active MoE) | 120B (12B active MoE) |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.2/1M in) across full 256K window | Flat rate ($0.3/1M in) across full 262K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Cached input at $0.06/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 74 GB VRAM (4-bit Quantized) · 258 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text, vision, audio | text |
| Output Modalities | text | text |
Nemotron 3 Nano Omni 30B A3B Reasoning vs Nemotron 3 Super 120B A12B: Quick Answers
Which is more intelligent, Nemotron 3 Nano Omni 30B A3B Reasoning or Nemotron 3 Super 120B A12B?
Nemotron 3 Super 120B A12B is more intelligent. It scores 53 compared with 48 on the composite Intelligence Index.
Which model is faster?
Nemotron 3 Nano Omni 30B A3B Reasoning is faster, generating 105 tokens per second compared with 85 tokens per second.
Which model is cheaper to run?
Nemotron 3 Nano Omni 30B A3B Reasoning is cheaper at $0.14 per 1M tokens blended, compared with $0.18 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nemotron 3 Nano Omni 30B A3B Reasoning has lower latency, with a time to first token of 0.38s compared with 0.46s.
Which model has a larger context window?
Nemotron 3 Super 120B A12B has a larger context window, supporting 262.1K tokens compared with 256K tokens.
Verdict
Verdict & Model Selection Recommendation: Choose Nemotron 3 Nano Omni 30B A3B Reasoning if your priority is Interactive robotics, smart camera analysis, and multimodal customer kiosks. Its performance in demanding tasks justifies its operational token cost. Choose Nemotron 3 Super 120B A12B if your workflow prioritizes Enterprise multi-agent architectures, massive data extraction, and autonomous coding. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Frequently asked questions
How does Nemotron 3 Nano Omni 30B A3B Reasoning compare to Nemotron 3 Super 120B A12B in API token pricing and cost per token?+
Nemotron 3 Nano Omni 30B A3B Reasoning costs $0.20 per 1M input tokens and $0.60 per 1M output tokens, whereas Nemotron 3 Super 120B A12B costs $0.30 input and $0.80 output. Overall, Nemotron 3 Nano Omni 30B A3B Reasoning is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Nemotron 3 Nano Omni 30B A3B Reasoning or Nemotron 3 Super 120B A12B?+
Nemotron 3 Nano Omni 30B A3B Reasoning supports a context window of 256K tokens (~192k words), while Nemotron 3 Super 120B A12B supports 262K tokens (~197k words). Therefore, Nemotron 3 Super 120B A12B can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Nemotron 3 Nano Omni 30B A3B Reasoning or Nemotron 3 Super 120B A12B?+
Nemotron 3 Nano Omni 30B A3B Reasoning scores 42% on SWE-bench Verified while Nemotron 3 Super 120B A12B scores 51%. For autonomous software engineering and multi-file debugging, Nemotron 3 Super 120B A12B holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Nemotron 3 Nano Omni 30B A3B Reasoning and Nemotron 3 Super 120B A12B?+
Nemotron 3 Nano Omni 30B A3B Reasoning features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Nemotron 3 Super 120B A12B provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Nemotron 3 Nano Omni 30B A3B Reasoning and Nemotron 3 Super 120B A12B?+
Nemotron 3 Nano Omni 30B A3B Reasoning generates approximately 105 tokens per second, while Nemotron 3 Super 120B A12B delivers 85 tokens per second. In latency-sensitive production environments, Nemotron 3 Nano Omni 30B A3B Reasoning provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Nemotron 3 Nano Omni 30B A3B Reasoning and Nemotron 3 Super 120B A12B to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Nemotron 3 Nano Omni 30B A3B Reasoning to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Nemotron 3 Super 120B A12B. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs