DeepSeek vs GPT-4o: API Cost Compared (2026)

DeepSeek V4-Flash bills input at $0.14 and output at $0.28 per million tokens, while OpenAI GPT-4o charges $2.50 and $10.00, so GPT-4o input runs about 18x and output about 36x more expensive than DeepSeek for the same token volume. That single ratio is the reason this comparison gets searched so often, and it holds up when you actually run both models on the same prompt rather than reading two pricing pages side by side.

We did run them. The short version: on raw price DeepSeek wins by a wide margin that no markup or routing trick erases, and the only question worth asking is whether GPT-4o's output earns its premium for your specific workload. Below is the rate card, our live coding test, and a verdict block that names when each model is the right call.

DeepSeek vs GPT-4o API cost (verified 2026-05)

According to DeepSeek API Docs, V4-Flash is priced at $0.14 per million input tokens and $0.28 per million output tokens, the model that the deepseek-chat alias now resolves to. GPT-4o sits an order of magnitude above it on both sides of the meter, which is the gap most buyers underestimate until they model a full month.

The output column is where the comparison turns lopsided. Input is roughly 18x more expensive on GPT-4o, but output is roughly 36x, and output is the side of the bill that grows when a model is chatty or reasons out loud. For any workload that generates long completions, the effective multiple lands closer to the output figure than the input one, because output tokens dominate the total.

According to Helicone's GPT-4o pricing reference, the $2.50 / $10.00 rate is OpenAI's standard published pricing, not a promotional or tiered number, so the gap above is the steady-state comparison rather than a temporary discount on either side. We cite the comparator rate from a third-party tracker because it aggregates OpenAI's posted price; the DeepSeek rate we confirmed directly against the official endpoint. According to DeepSeek API Docs, deepseek-chat resolves to V4-Flash, so the $0.14 / $0.28 row is the rate you actually pay even when calling the legacy alias name.

What the gap does to a real monthly bill

Numbers per million tokens feel abstract, so anchor them. Take a service generating 200 million output tokens a month, a modest volume for a production chat product. On DeepSeek V4-Flash that output costs $56. On GPT-4o the same 200 million output tokens cost $2,000. The input side widens it further but matters less because output is usually the larger share. That is not a rounding difference you optimize away with caching or batching; it is a structural 36x on the line item that scales with usage.

The practical upshot is that DeepSeek changes which products are even viable. A summarization or drafting feature that would lose money at GPT-4o output rates can run comfortably at DeepSeek rates, which is why the price comparison is really a product-feasibility question dressed up as a procurement one.

We ran the same coding prompt on both (first-hand evidence)

Pricing pages tell you the rate. They do not tell you how many tokens each model actually spends to answer, and that token count is half of what you pay. So we sent both models one identical prompt, "Write a Python function returning the nth Fibonacci number iteratively. Code only," and recorded the raw usage objects from each API.

The GPT-4o and Claude calls were routed through OpenRouter, so we disclose that the comparator latency and billing carry whatever OpenRouter adds on top of OpenAI's and Anthropic's own rates. DeepSeek ran on its first-party endpoint. On that GPT-4o run OpenRouter billed us $0.000795 for 34 input and 71 output tokens, a real charge against a real key, not a calculator estimate.

One result surprised us enough that we re-read the usage object twice. DeepSeek V4-Flash spent 120 output tokens to GPT-4o's 71, because V4-Flash emitted reasoning tokens (119 of the 120) before the code. So the token-count advantage on this prompt actually went to GPT-4o, which answered more tersely. Even so, at $0.28 per million versus $10.00, DeepSeek's 120 output tokens cost a tiny fraction of GPT-4o's 71. The price gap is so large it swamps a nearly 2x token-count disadvantage, which is exactly the point: you can let DeepSeek be verbose and still pay less.

When the cost gap justifies DeepSeek, and when GPT-4o still wins

Choose DeepSeek V4-Flash when output volume is high and the task is well-specified: bulk summarization, classification, code scaffolding, retrieval-augmented chat with a stable system prompt. At 36x cheaper output, it turns features that were uneconomical into ones that ship. Avoid leaning on it for tasks where a subtle quality regression is expensive, such as nuanced reasoning over ambiguous instructions or polished customer-facing copy, where GPT-4o's tighter, less verbose output can still justify its premium.

The honest verdict is that this is rarely a tie. For the vast majority of high-volume API workloads the price gap decides it, and DeepSeek wins. GPT-4o earns its 18-to-36x premium only when output quality on your specific task measurably moves a business metric, and the way to know is to run your own prompts against both, the way we ran ours, rather than trusting either vendor's benchmark chart.

If US data residency is a hard requirement, route DeepSeek through a US provider and accept a markup, a tradeoff covered in our note on whether DeepSeek is available in the US. For the full rate card and the rest of this analysis, see the DeepSeek API pricing hub.

FAQ

How much cheaper is DeepSeek than GPT-4o per token? DeepSeek V4-Flash costs $0.14 input and $0.28 output per million tokens against GPT-4o's $2.50 and $10.00. That makes GPT-4o input about 18x more expensive and output about 36x more expensive for the same token volume, with the output multiple being the one that dominates real bills.

Did DeepSeek actually use fewer tokens than GPT-4o in your test? No, the opposite. On our identical Fibonacci prompt, DeepSeek V4-Flash spent 120 output tokens while GPT-4o spent 71, because V4-Flash emitted reasoning tokens first. Despite using more tokens, DeepSeek still cost a fraction of GPT-4o because its output rate is 36x lower.

What did GPT-4o cost in your live run? OpenRouter billed our GPT-4o call $0.000795 for 34 input and 71 output tokens. We disclose that this was routed through OpenRouter rather than called on OpenAI directly, so it reflects whatever margin that router adds on top of OpenAI's published $2.50 / $10.00 rate.

Is GPT-4o ever worth the premium over DeepSeek? It can be when output quality on a specific task moves a business metric, such as customer-facing copy or reasoning over ambiguous instructions. For high-volume, well-specified workloads like summarization or code scaffolding, the 18-to-36x price gap almost always favors DeepSeek.

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This is part of the DeepSeek API pricing hub. For the side of the bill that grows fastest, see our note on input vs output pricing.

Author: Kevin Fan, Customer Success Manager at China LLM Directory, specializing in Chinese LLM ecosystem pricing. Last verified: 2026-05-13.

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