| Signal | Llama 4 Maverick | Delta | Nemotron 3 Super |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 80 | +80 | |
Pricing | 1 | +0 | |
Context window size | 96 | +10 | |
Recency | 69 | -31 | |
Output Capacity | 70 | +50 | |
| Overall Result | 4 wins | of 6 | 1 wins |
22
days ranked higher
5
days
3
days ranked higher
Meta
NVIDIA
Nemotron 3 Super saves you $10.00/month
That's $120.00/year compared to Llama 4 Maverick at your current usage level of 100K calls/month.
| Metric | Llama 4 Maverick | Nemotron 3 Super | Winner |
|---|---|---|---|
| Overall Score | 77 | 74 | Llama 4 Maverick |
| Rank | #99 | #120 | Llama 4 Maverick |
| Quality Rank | #99 | #120 | Llama 4 Maverick |
| Adoption Rank | #99 | #120 | Llama 4 Maverick |
| Parameters | -- | 120B | -- |
| Context Window | 1049K | 262K | Llama 4 Maverick |
| Pricing | $0.15/$0.60/M | $0.10/$0.50/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Llama 4 Maverick |
| Benchmarks | 80 | -- | Llama 4 Maverick |
| Pricing | 1 | 1 | Llama 4 Maverick |
| Context window size | 96 | 86 | Llama 4 Maverick |
| Recency | 69 | 100 | Nemotron 3 Super |
| Output Capacity | 70 | 20 | Llama 4 Maverick |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 77/100 (rank #99), placing it in the top 66% of all 290 models tracked.
Scores 74/100 (rank #120), placing it in the top 59% of all 290 models tracked.
With only a 3-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Nemotron 3 Super offers 20% better value per quality point. At 1M tokens/day, you'd spend $9.00/month with Nemotron 3 Super vs $11.25/month with Llama 4 Maverick - a $2.25 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Nemotron 3 Super also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.50/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (77/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Llama 4 Maverick has a moderate advantage with a 3.200000000000003-point lead in composite score. It wins on more signal dimensions, but Nemotron 3 Super has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Llama 4 Maverick
Marginally better benchmark scores; both are excellent
Best for Cost
Nemotron 3 Super
20% lower pricing; better value at scale
Best for Reliability
Llama 4 Maverick
Higher uptime and faster response speeds
Best for Prototyping
Llama 4 Maverick
Stronger community support and better developer experience
Best for Production
Llama 4 Maverick
Wider enterprise adoption and proven at scale
by Meta
| Capability | Llama 4 Maverick | Nemotron 3 Super |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Meta
NVIDIA
Nemotron 3 Super saves you $0.2100/month
That's 21% cheaper than Llama 4 Maverick at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Llama 4 Maverick | Nemotron 3 Super |
|---|---|---|
| Context Window | 1.0M | 262K |
| Max Output Tokens | 16,384 | -- |
| Open Source | Yes | Yes |
| Created | Apr 5, 2025 | Mar 11, 2026 |
Llama 4 Maverick scores 77/100 (rank #99) compared to Nemotron 3 Super's 74/100 (rank #120), giving it a 3-point advantage. Llama 4 Maverick is the stronger overall choice, though Nemotron 3 Super may excel in specific areas like cost efficiency.
Llama 4 Maverick is ranked #99 and Nemotron 3 Super is ranked #120 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Nemotron 3 Super is cheaper at $0.50/M output tokens vs Llama 4 Maverick's $0.60/M output tokens - 1.2x more expensive. Input token pricing: Llama 4 Maverick at $0.15/M vs Nemotron 3 Super at $0.10/M.
Llama 4 Maverick has a larger context window of 1,048,576 tokens compared to Nemotron 3 Super's 262,144 tokens. A larger context window means the model can process longer documents and conversations.