gpt-5.6-luna
Input price$0.2
Output price$1.2
OpenAITextVision
gpt-5.4-nano
gpt-5.4-nano is OpenAI's model at $0.20 input and $1.25 output per million tokens, with a 1049K context window. On a typical 3:1 input-to-output mix that blends to roughly $0.46 per million tokens, placing it in the budget band of the 68 models tracked here — cheaper than 70% of them.
Context window1049K
Input price$0.2 / 1M
Output price$1.25 / 1M
Output speed200 tok/s
Quality score75
Data updatedUpdated Jun 2026
Price verified2026-08-19 · Official
By price, gpt-5.4-nano ranks 16th cheapest of 68 on input and 27th on output. Its quality score of 75 ranks 61st of 68, and on value (quality score ÷ output price) it ranks 28th of 68. Its blended rate sits 84% below the catalog average.
In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $51 per month on gpt-5.4-nano, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $52. Because output is priced 6.3× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.
A 1049K context window holds roughly 1,399 pages of A4 text (at ~750 tokens per page), ranking 2nd of 68 here. That is enough to drop in an entire technical manual or several source files at once, which suits long-document summarization and codebase-wide analysis. Output runs at about 200 tok/s (5th fastest of 68), fast enough for real-time interaction and high-throughput batches.
We track 11 OpenAI models, and gpt-5.4-nano's blended rate sits 88% below that provider's average. If your task tolerates a little less headroom, qwen3.5-flash (Alibaba) blends about 88% cheaper at a quality score of 82, and is worth benchmarking first. Going the other way, Phi-4 scores 76 on quality for about 81% less.
The closest model in OpenAI's line-up is gpt-5.6-luna ($0.20 input / $1.20 output, quality 90). Against it, gpt-5.4-nano scores 15 points lower on quality, runs 50 tok/s faster (about 33%), costs 3% more blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.
Estimated monthly cost
Monthly API spend across four common workloads, next to the cheapest model we track.
| Workload | Usage assumption | This model | Cheapest model |
|---|---|---|---|
| Support chatbot | 2,000 input / 500 output tokens per turn, 50,000 turns per month | $51 | $3.00 |
| RAG document Q&A | 8,000 input / 800 output tokens per query, 20,000 queries per month | $52 | $3.84 |
| Coding assistant | 12,000 input / 2,000 output tokens per request, 10,000 requests per month | $49 | $3.20 |
| Batch summarization | 4,000 input / 400 output tokens per item, 200,000 items per month | $260 | $19 |
Derived directly from the rates on this page. Excludes prompt caching, batch discounts and free tiers.
How it compares
The alternatives worth benchmarking alongside it, from the same dataset.
| Model | Provider | Blended /1M | Quality | Price delta |
|---|---|---|---|---|
| gpt-5.4-nano | OpenAI | $0.46 | 75 | — |
| qwen3.5-flashCheaper option | Alibaba | $0.055 | 82 | -88% |
| Phi-4Higher quality | Microsoft | $0.088 | 76 | -81% |
| gpt-5.6-lunaSame provider | OpenAI | $0.45 | 90 | -3% |
| Phi-4-miniBest value overall | Microsoft | $0.025 | 68 | -95% |
Best for
ChatbotAffordableFast
Modalities
TextVision
Where it fits — and where it doesn't
Good fit
- Chat and support: natural multi-turn conversation for user-facing products.
- Long documents: a 1049K window ingests a full contract, paper or large codebase in one pass.
- High throughput and real-time UX: 200 tok/s keeps streamed responses feeling instant.
- High-volume, cost-sensitive batch work: low rates suit classification, tagging and summarization at scale.
- Multimodal input: handles images, screenshots and scanned documents directly.
Poor fit
- Hard reasoning: a quality score of 75 is on the low side here; pick a stronger model for complex planning or maths.
Frequently asked questions
How much does the gpt-5.4-nano API cost?
gpt-5.4-nano costs $0.20 per million input tokens and $1.25 per million output tokens. On a 3:1 input-to-output mix that blends to about $0.46 per million tokens.
What does gpt-5.4-nano cost per month?
It depends on volume. Using the four worked scenarios on this page: a support chatbot runs about $51/month, RAG document Q&A about $52/month, a coding assistant about $49/month, and batch summarization about $260/month. Plug your own token counts into the cost calculator for a tailored figure.
How large is the gpt-5.4-nano context window?
1049K tokens — roughly 1,399 pages of A4 text at ~750 tokens per page, ranking 2nd of the 68 models tracked here.
gpt-5.4-nano or qwen3.5-flash — which is better value?
qwen3.5-flash blends to about $0.055 per million tokens versus $0.46 for gpt-5.4-nano — roughly 88% cheaper — at a quality score of 82 against 75. If that quality gap does not show up on your task, take the cheaper one; if it does, stay with gpt-5.4-nano. Benchmark both on your own data before deciding.
What is gpt-5.4-nano best suited for?
Tagged use cases: chatbot, cheap, fast. Chat and support: natural multi-turn conversation for user-facing products. Less suitable: Hard reasoning: a quality score of 75 is on the low side here; pick a stronger model for complex planning or maths.
How current is this gpt-5.4-nano pricing?
Pricing here was last verified on 2026-08-19 against official documentation. llmprice.app runs a daily collection job, but providers can change rates between runs — confirm against OpenAI's official pricing page before you commit.
Estimate the real cost of this model
Bring tokens per request and monthly volume into the calculator to compare total model costs.
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Pricing, speed and quality scores change over time. Confirm official documentation before production use.