Nemotron vs Llama: Open Model Comparison
Compare NVIDIA Nemotron 3 Ultra and Meta Llama 4 Scout on architecture, ₹ pricing and availability on unoblox.
NVIDIA's Nemotron and Meta's Llama 4 are both open-weight model families available on unoblox, but only one of them has a fixed ₹ rate in the current price list. Here's what's actually known and priced today.
What the model ids tell you
nvidia/nemotron-3-ultra-550b-a55b and meta-llama/llama-4-scout-17b-16e-instruct both encode architecture details in their names — a common convention where the first number is total parameters and a suffix like "a55b" or the expert count points to a mixture-of-experts design with a smaller active-parameter count per token. Treat that as a naming convention, not a performance claim — the only way to know how a model behaves on your workload is to test it directly.
₹ pricing: what's fixed and what isn't
| Model | Model id | Input (₹ / 1M tokens) | Output (₹ / 1M tokens) |
|---|---|---|---|
| Nemotron 3 Ultra | nvidia/nemotron-3-ultra-550b-a55b | ₹50.61 | ₹222.70 |
| Llama 4 Scout | meta-llama/llama-4-scout-17b-16e-instruct | ₹10.12 | ₹30.36 |
Rates are as of 6 October 2026; check each live model page (for example https://unoblox.ai/models/nvidia/nemotron-3-ultra-550b-a55b) before estimating cost for a production workload. Llama 4 Maverick is not currently offered on unoblox.
Choosing between a large MoE model and Llama 4
- If your priority is a known, fixed ₹ cost you can budget against today, Llama 4 Scout is the cheaper starting point.
- If you specifically want to evaluate Nemotron's larger architecture for a demanding task, test it first at low volume and confirm its live rate before scaling up — don't assume it's priced similarly to Llama.
- For most general-purpose text tasks, start with the cheaper Llama 4 Scout and only move to a larger model if your evaluation shows a real quality gap on your own prompts.
Same request shape for both families
curl https://api.unoblox.ai/v1/chat/completions \
-H "Authorization: Bearer ub-gw-xxxxxxxxxxxxxxxx" \
-H "Content-Type: application/json" \
-d '{"model":"meta-llama/llama-4-scout-17b-16e-instruct","messages":[{"role":"user","content":"Summarise this report in three bullet points."}]}'
Change "model" to nvidia/nemotron-3-ultra-550b-a55b to test the same prompt on Nemotron — same key, same endpoint, one GST invoice covering both.
Frequently asked questions
Is Nemotron cheaper or more expensive than Llama 4? Nemotron 3 Ultra (₹50.61 / ₹222.70) costs more than Llama 4 Scout (₹10.12 / ₹30.36) on both input and output tokens.
What does the "550b-a55b" naming mean? It's a common shorthand for a mixture-of-experts model's total parameter count versus its active parameters per token — a naming convention, not a guarantee of relative quality against Llama.
Are Nemotron and Llama hosted on infrastructure in India? No, both run on their standard hosting behind unoblox's endpoint. The India benefit is ₹ billing, a GST invoice and one endpoint — not data residency for these models.
Which Llama 4 model should I start with? Llama 4 Scout — it is the Llama 4 model offered on unoblox and a reasonable low-cost baseline.
Can I test Nemotron without committing to production volume? Yes — call it like any other model with your existing key at low volume, and confirm the live ₹ rate before scaling.
Do open-weight models like these get updated over time? Providers do update model versions; always check the model's live page for the current id and rate rather than assuming past pricing still applies.
Get started in rupees → https://unoblox.ai/sign-in
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