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Daily blended price ($/1M) — recorded each day, builds into a trend over time.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-11 · Source: nvidia_reference_catalog
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
Llama-3.3-Nemotron-Super-49B-v1.5 is a 49B-parameter, English-centric reasoning/chat model derived from Meta’s Llama-3.3-70B-Instruct with a 128K context. It’s post-trained for agentic workflows (RAG, tool calling) vi...
llama-3.3-nemotron-super-49b-v1.5 is a Text model from NVIDIA (US). HotON.ai tracks it at $0.10 per 1M input tokens and $0.40 per 1M output tokens, with a 131K-token context window. Its composite efficiency score is 89/100 at an estimated $0.000 per successful task.
llama-3.3-nemotron-super-49b-v1.5 is tracked at $0.10 per 1M input tokens and $0.40 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.33 per 1M tokens. Figures are illustrative demo data.
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
llama-3.3-nemotron-super-49b-v1.5 supports up to a 131K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, llama-3.3-nemotron-super-49b-v1.5 is cheaper than 79% of models on input price and ranks #264 of 537 by overall efficiency.
Yes — deepseek/deepseek-v4-flash is a lower-cost option at $0.28 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
Ready to paste into articles, papers or AI prompts — prices and date refresh with the live data.
HotON.ai — llama-3.3-nemotron-super-49b-v1.5 (NVIDIA): $0.10/1M input, $0.40/1M output, as of 2026-05-11. https://hoton.ai/en/models/nvidia-llama-3-3-nemotron-super-49b-v1-5Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.