Which is cheaper, DeepSeek-V4-Pro-Max or GPT-4.1 nano?
As of August 20, 2026, GPT-4.1 nano is 90% cheaper on blended LLM API pricing. GPT-4.1 nano costs $0.10 per million input tokens and $0.40 per million output tokens ($0.50 blended 1M-in + 1M-out). DeepSeek-V4-Pro-Max costs $1.74 / $3.48 per million tokens ($5.22 blended). Sources: https://api-docs.deepseek.com/quick_start/pricing and https://developers.openai.com/api/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does DeepSeek-V4-Pro-Max vs GPT-4.1 nano cost per million tokens?
DeepSeek-V4-Pro-Max DeepSeek API pricing is $1.74 input and $3.48 output per million tokens via DeepSeek. GPT-4.1 nano OpenAI API pricing is $0.10 input and $0.40 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, DeepSeek-V4-Pro-Max or GPT-4.1 nano?
DeepSeek-V4-Pro-Max has a published SWE-bench Verified score of 80.6%. GPT-4.1 nano does not have that eval on this page yet.
What is the context window for DeepSeek-V4-Pro-Max vs GPT-4.1 nano?
DeepSeek-V4-Pro-Max supports a 1M token context window, while GPT-4.1 nano supports 1M tokens. DeepSeek-V4-Pro-Max 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, DeepSeek-V4-Pro-Max or GPT-4.1 nano?
DeepSeek-V4-Pro-Max leads on 7 of 7 shared benchmarks versus GPT-4.1 nano's 0 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 DeepSeek-V4-Pro-Max or GPT-4.1 nano better for production use?
Both DeepSeek-V4-Pro-Max and GPT-4.1 nano are production API models. For cost-sensitive production traffic, GPT-4.1 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 DeepSeek-V4-Pro-Max and GPT-4.1 nano in my app?
Yes. Call DeepSeek-V4-Pro-Max through DeepSeek and GPT-4.1 nano through OpenAI 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 DeepSeek-V4-Pro-Max vs GPT-4.1 nano pricing data?
List rates are the latest published DeepSeek API pricing and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://api-docs.deepseek.com/quick_start/pricing and https://developers.openai.com/api/docs/pricing. 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 DeepSeek-V4-Pro-Max and GPT-4.1 nano?
DeepSeek-V4-Pro-Max supports up to 131K output tokens per request, while GPT-4.1 nano supports up to 33K 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, DeepSeek-V4-Pro-Max or GPT-4.1 nano?
GPT-4.1 nano has a measured throughput of approximately 200 tokens/second. Throughput data for DeepSeek-V4-Pro-Max is not yet available. 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 DeepSeek-V4-Pro-Max vs GPT-4.1 nano comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open DeepSeek-V4-Pro-Max or GPT-4.1 nano from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
