Nemotron 3 Super vs Llama 4 Maverick
Comprehensive comparison between NVIDIA's Nemotron 3 Super and Meta's Llama 4 Maverick. Compare pricing, performance, features, and user reviews.
Nemotron 3 Super
NVIDIANVIDIA's flagship open-source model for agentic AI, featuring 120B total parameters with 12B active (MoE). Hybrid Mamba-Transformer architecture delivers 5x throughput vs previous Nemotron Super. 1M context window prevents goal drift in complex multi-agent workflows. #1 on DeepResearch Bench.
Llama 4 Maverick
MetaMeta's flagship open-source multimodal model. 17B active parameters with 400B total (128 expert MoE). 1M context window, natively multimodal with early fusion. Extremely cost-effective at $0.15/$0.60 per M tokens. Supports 12 languages.
Specs Comparison
| Specification | Nemotron 3 Super | Llama 4 Maverick |
|---|---|---|
| Context Window | 1000K | 1049K |
| Max Output | 40K | 16K |
| Input (per 1M tokens) | $0.40 | $0.15 |
| Output (per 1M tokens) | $2.20 | $0.60 |
| Reasoning | ||
| Open Source |
Scenario Score Comparison
Nemotron 3 Super
Pros
- + 1M context window for full workflow state
- + 5x throughput vs previous Nemotron Super
- + Open weights under permissive license
- + #1 on DeepResearch Bench I & II
- + Multi-token prediction for 3x faster inference
Cons
- − Text-only (no multimodal support)
- − Requires high-end hardware for self-hosting
- − New release, limited community feedback
Llama 4 Maverick
Pros
- + Extremely affordable ($0.15/$0.60)
- + 1M context window
- + Native multimodal (text + image)
- + Open source (Llama 4 Community License)
- + High throughput MoE architecture
Cons
- − Coding performance below Claude/GPT
- − Benchmark gaming controversy
- − 16K max output limit
- − Knowledge cutoff August 2024
Recommendation
Choose Nemotron 3 Super if you:
- • Need 1m context window for full workflow state
- • Need 5x throughput vs previous nemotron super
- • Need open weights under permissive license
Choose Llama 4 Maverick if you:
- • Need extremely affordable ($0.15/$0.60)
- • Need 1m context window
- • Need native multimodal (text + image)
Based on scores across 0 scenarios, both models perform equally well.
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💡 Open source - can be self-hosted or used via API providers.
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