A powerful, open-weight model from NVIDIA, balancing strong intelligence with competitive pricing and impressive speed, particularly suited for non-reasoning tasks.
The Llama Nemotron Super 49B v1.5 (Non-reasoning) emerges as a compelling offering in the landscape of large language models, particularly for applications that prioritize efficiency and cost-effectiveness over complex multi-step reasoning. Developed by NVIDIA, this open-weight model distinguishes itself with an above-average intelligence score, competitive pricing, and impressive output speed. It is designed to handle a broad spectrum of text-based tasks, from content generation to summarization, leveraging its substantial 128k token context window to process extensive inputs.
Scoring 27 on the Artificial Analysis Intelligence Index, Llama Nemotron Super 49B v1.5 positions itself notably above the average of 22 for comparable models. This indicates a robust capability in understanding and generating coherent, relevant text, even if its primary design is not for deep reasoning. While demonstrating strong intelligence, the model does exhibit a tendency towards verbosity, generating 9.8 million tokens during its Intelligence Index evaluation, which is somewhat higher than the 8.5 million token average. This characteristic is important for users to consider when managing output length and associated costs.
From a financial perspective, Llama Nemotron Super 49B v1.5 offers an attractive pricing structure. Input tokens are priced at $0.10 per 1 million tokens, which is moderately priced and significantly below the average of $0.20. Output tokens are set at $0.40 per 1 million tokens, also moderately priced compared to the average of $0.54. When blended at a 3:1 ratio (input:output), the effective price is $0.17 per 1 million tokens. This competitive pricing, combined with its performance, makes it an economical choice for many high-volume applications. The total cost to evaluate the model on the Intelligence Index was $11.64, further underscoring its value proposition.
Performance-wise, the model excels in speed, delivering an impressive 69 tokens per second, surpassing the average of 60 tokens per second. This high output speed ensures rapid content generation and efficient processing of requests. Furthermore, its low latency of 0.25 seconds for the time to first token (TTFT) means users experience quick initial responses, enhancing the interactivity and responsiveness of applications built upon it. With its open license and NVIDIA backing, Llama Nemotron Super 49B v1.5 provides a powerful, accessible, and economically viable solution for a wide array of non-reasoning text generation and processing needs.
27 (#9 / 33 / 49B)
69 tokens/s
$0.10 /M tokens
$0.40 /M tokens
9.8M tokens
0.25 s
| Spec | Details |
|---|---|
| Owner | NVIDIA |
| License | Open |
| Context Window | 128k tokens |
| Model Size | 49B parameters |
| Input Type | Text |
| Output Type | Text |
| Primary Use Case | Non-reasoning tasks |
| Intelligence Index Score | 27 |
| Output Speed (Deepinfra) | 69 tokens/s |
| Latency (Deepinfra) | 0.25 seconds |
| Input Price (Deepinfra) | $0.10 / 1M tokens |
| Output Price (Deepinfra) | $0.40 / 1M tokens |
| Blended Price (Deepinfra) | $0.17 / 1M tokens (3:1 blend) |
For Llama Nemotron Super 49B v1.5 (Non-reasoning), Deepinfra stands out as the primary benchmarked provider, offering a balanced performance profile that aligns well with the model's strengths. While the market for this model may expand, our current data highlights Deepinfra's competitive offering for users seeking a reliable and efficient deployment.
| Priority | Pick | Why | Tradeoff to accept |
|---|---|---|---|
| Balanced Performance | Deepinfra | Offers a strong combination of competitive pricing ($0.17/M blended), impressive output speed (69 tokens/s), and low latency (0.25s). | Currently the sole benchmarked provider, limiting direct comparison options for users. |
Performance and pricing data are based on current benchmarks and may vary with future updates or different providers. Always verify the latest offerings.
Understanding the practical implications of Llama Nemotron Super 49B v1.5's performance and pricing requires examining its behavior across various real-world scenarios. The following examples illustrate its estimated cost and efficiency for common tasks, leveraging its strengths in speed and context handling.
| Scenario | Input | Output | What it represents | Estimated cost |
|---|---|---|---|---|
| Content Generation (Blog Post) | 500 tokens | 1,500 tokens | Standard content creation, marketing copy, article drafting. | $0.00065 |
| Summarization (Long Document) | 100,000 tokens | 2,000 tokens | Enterprise document analysis, research paper summarization within its large context window. | $0.01080 |
| Chatbot Response (Short Exchange) | 100 tokens | 50 tokens | Interactive customer support, quick Q&A, brief conversational turns. | $0.00003 |
| Data Extraction (Structured Output) | 5,000 tokens | 1,000 tokens | Parsing unstructured text data into structured formats like JSON. | $0.00090 |
| Code Generation (Function) | 2,000 tokens | 800 tokens | Developer assistance, generating boilerplate code snippets or simple functions. | $0.00052 |
Llama Nemotron Super 49B v1.5 demonstrates cost-effectiveness across a range of common non-reasoning tasks, with its large context window making it particularly efficient for processing substantial inputs like document summarization without incurring prohibitive costs.
Optimizing costs with Llama Nemotron Super 49B v1.5 involves strategic prompt engineering and output management, leveraging its strengths in speed and context while mitigating its tendency towards verbosity.
Crafting precise and concise prompts is crucial for maximizing cost-efficiency. While Llama Nemotron Super 49B v1.5 has a large context window, unnecessary input tokens still contribute to cost. Focus on providing only the essential information needed for the model to generate the desired output.
Given the model's moderate output token price and its tendency towards verbosity, actively managing the length of generated outputs is key. Implement strategies to encourage conciseness and truncate outputs when necessary to avoid paying for superfluous text.
Llama Nemotron Super 49B v1.5's high output speed (69 tokens/s) is a significant advantage for applications requiring rapid processing of many requests. Design your workflows to capitalize on this speed, especially for batch processing or real-time applications where quick turnaround is essential.
The 128k token context window is a powerful feature, allowing the model to process and understand very long documents or extensive conversational histories. Utilize this capacity strategically for tasks that genuinely benefit from broad contextual awareness, such as detailed summarization or comprehensive data extraction.
Regularly monitor your API usage and analyze the token consumption patterns. This data is invaluable for identifying areas of inefficiency and refining your prompting strategies to reduce costs over time.
Llama Nemotron Super 49B v1.5 (Non-reasoning) is a large, open-weight language model developed by NVIDIA. It is designed for efficient text generation and processing tasks, excelling in areas that do not require complex, multi-step reasoning, such as content creation, summarization, and data extraction.
Its key strengths include above-average intelligence (scoring 27 on the Intelligence Index), impressive output speed (69 tokens/s), low latency (0.25s TTFT), a large 128k token context window, and competitive pricing for both input and output tokens. Its open-weight nature also fosters flexibility and community integration.
Llama Nemotron Super 49B v1.5 offers competitive pricing, with input tokens at $0.10/1M and output tokens at $0.40/1M. These rates are moderately priced and generally below the average for comparable models, making it a cost-effective choice for many applications.
The model boasts a substantial 128k token context window. This allows it to process and understand very long inputs, making it highly suitable for tasks like summarizing extensive documents or maintaining long conversational histories.
As indicated by its "(Non-reasoning)" variant tag, Llama Nemotron Super 49B v1.5 is not primarily designed for complex, multi-step reasoning tasks. While intelligent, its strengths lie in efficient text generation and processing where deep logical inference is not the main requirement.
Llama Nemotron Super 49B v1.5 is owned by NVIDIA and is released under an open license. This open-weight status provides developers and organizations with greater flexibility for deployment, customization, and integration into various projects.
The model demonstrates excellent performance with an output speed of 69 tokens per second, which is faster than average. It also features a very low latency of 0.25 seconds for the time to first token (TTFT), ensuring quick initial responses for interactive applications.