Which is cheaper, GPT-5.4 nano or Llama 3.1 Nemotron Ultra 253B v1?
As of August 30, 2026, GPT-5.4 nano is 40% cheaper on blended LLM API pricing. GPT-5.4 nano costs $0.20 per million input tokens and $1.25 per million output tokens ($1.45 blended 1M-in + 1M-out). Llama 3.1 Nemotron Ultra 253B v1 costs $0.60 / $1.80 per million tokens ($2.40 blended). Sources: https://developers.openai.com/api/docs/pricing and https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-5.4 nano vs Llama 3.1 Nemotron Ultra 253B v1 cost per million tokens?
GPT-5.4 nano OpenAI API pricing is $0.20 input and $1.25 output per million tokens via OpenAI. Llama 3.1 Nemotron Ultra 253B v1 NVIDIA API pricing is $0.60 input and $1.80 output per million tokens via NVIDIA. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT-5.4 nano or Llama 3.1 Nemotron Ultra 253B v1?
GPT-5.4 nano has a published SWE-bench Verified score of 69.8%. Llama 3.1 Nemotron Ultra 253B v1 does not have that eval on this page yet.
What is the context window for GPT-5.4 nano vs Llama 3.1 Nemotron Ultra 253B v1?
GPT-5.4 nano supports a 400K token context window, while Llama 3.1 Nemotron Ultra 253B v1 supports 131K tokens. GPT-5.4 nano offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, GPT-5.4 nano or Llama 3.1 Nemotron Ultra 253B v1?
GPT-5.4 nano leads on 2 of 3 shared benchmarks versus Llama 3.1 Nemotron Ultra 253B v1's 1 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is GPT-5.4 nano or Llama 3.1 Nemotron Ultra 253B v1 better for production use?
Both GPT-5.4 nano and Llama 3.1 Nemotron Ultra 253B v1 are production API models. For cost-sensitive production traffic, GPT-5.4 nano has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between GPT-5.4 nano and Llama 3.1 Nemotron Ultra 253B v1 in my app?
Yes. Call GPT-5.4 nano through OpenAI and Llama 3.1 Nemotron Ultra 253B v1 through NVIDIA with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this GPT-5.4 nano vs Llama 3.1 Nemotron Ultra 253B v1 pricing data?
List rates are the latest published OpenAI API pricing and NVIDIA API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for GPT-5.4 nano and Llama 3.1 Nemotron Ultra 253B v1?
GPT-5.4 nano supports up to 128K output tokens per request, while Llama 3.1 Nemotron Ultra 253B v1 supports up to an unspecified number of output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, GPT-5.4 nano or Llama 3.1 Nemotron Ultra 253B v1?
Neither GPT-5.4 nano nor Llama 3.1 Nemotron Ultra 253B v1 has published throughput data on this page yet. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this GPT-5.4 nano vs Llama 3.1 Nemotron Ultra 253B v1 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-5.4 nano or Llama 3.1 Nemotron Ultra 253B v1 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
