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by VibecodedThis

GPT-5.4 Mini and Nano: OpenAI Brings Flagship Capabilities to Its Cheapest Models

OpenAI releases GPT-5.4 Mini and GPT-5.4 Nano with 400K context, computer use support, and pricing starting at $0.20 per million tokens. Here's what developers actually get.

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OpenAI shipped two new models today: GPT-5.4 Mini and GPT-5.4 Nano. Both are smaller, cheaper versions of the GPT-5.4 flagship that launched on March 5. OpenAI calls them “our most capable small models yet,” and the specs back that up. Mini gets computer use. Nano costs less than a quarter per million input tokens. Both share the same 400K context window and 128K max output.

The pitch from OpenAI is straightforward: these models “come close to matching the default GPT-5.4 model’s abilities at coding and agentically operating software,” just at a fraction of the cost and with significantly lower latency.

Two Models, Two Jobs

GPT-5.4 Mini (gpt-5.4-mini) is the workhorse. OpenAI describes it as their “strongest mini model yet for coding, computer use, and subagents.” It supports the full tool stack, including computer use and tool search, the two headline features from the GPT-5.4 launch. It runs more than twice as fast as GPT-5.0 Mini while scoring better on reasoning, multimodal understanding, and tool use.

In ChatGPT, Mini is now available to Free and Go users through the “Thinking” option in the model picker. Paid users on Plus, Team, and Pro plans will see it as a fallback when they hit rate limits on the full GPT-5.4.

GPT-5.4 Nano (gpt-5.4-nano) is the speed demon. OpenAI positions it as “our cheapest GPT-5.4-class model for simple high-volume tasks.” Think data classification, extraction, ranking, and sub-agent work where a bigger model decides what to do and nano executes thousands of times per day. It’s API-only, so you won’t find it in ChatGPT.

The key capability difference: Mini gets computer use and tool search. Nano does not. Both support function calling, structured outputs, web search, file search, code interpreter, MCP, and vision (image input).

Pricing

The full GPT-5.4 family now spans four price points, from $0.20 to $30 per million input tokens.

ModelInput / 1MCached Input / 1MOutput / 1M
GPT-5.4$2.50$0.25$15.00
GPT-5.4 Mini$0.75$0.075$4.50
GPT-5.4 Nano$0.20$0.02$1.25
GPT-5.4 Pro$30.00$180.00

Batch API pricing cuts those rates roughly in half: Mini drops to $0.375 input / $2.25 output, and Nano to $0.10 input / $0.625 output.

Compared to the full GPT-5.4, Mini is about 70% cheaper on input and output. Nano is 92% cheaper. Both offer 90% discounts on cached inputs, which matters a lot for agent loops that hit the same context repeatedly.

Technical Specs

Both models share the same architecture envelope:

SpecGPT-5.4 MiniGPT-5.4 Nano
Context window400,000 tokens400,000 tokens
Max output128,000 tokens128,000 tokens
Knowledge cutoffAugust 31, 2025August 31, 2025
Input modalitiesText, imagesText, images
Output modalitiesTextText
ReasoningAdjustable (none to extra-high)Adjustable (none to extra-high)
Computer useYesNo
Tool searchYesNo
MCPYesYes
Structured outputsYesYes
Function callingYesYes
DistillationYesYes
Fine-tuningNoNo

The 400K context window is notable. The original GPT-5 Mini and Nano (from August 2025) also had 400K context, so this isn’t new. But it’s still a generous window for models at this price point.

The Cost of an Upgrade

Here’s the part OpenAI isn’t highlighting: these models are significantly more expensive than the GPT-5 Mini and Nano they replace.

ModelOld Price (Input)New Price (Input)Increase
Mini$0.25/1M$0.75/1M3x
Nano$0.05/1M$0.20/1M4x

Output tokens tell a similar story. Mini went from $2.00 to $4.50 per million. Nano from $0.40 to $1.25.

OpenAI’s argument is that you’re getting GPT-5.4-class capabilities at these prices, not just a warmed-over GPT-5. If the performance is genuinely close to the flagship, that’s a reasonable trade. But developers running high-volume pipelines on the old GPT-5 Nano at five cents per million tokens will feel the jump.

What We Don’t Know Yet

Since both models launched today, no independent benchmark data exists for GPT-5.4 Mini or Nano. OpenAI hasn’t published specific scores for SWE-Bench, GPQA, or other standard evaluations on these variants.

For reference, the GPT-5 predecessors (August 2025) posted these numbers:

BenchmarkGPT-5 MiniGPT-5 Nano
AIME 202591.1%85.2%
GPQA82.3%71.2%
HMMT 202587.8%75.6%
Humanity’s Last Exam16.7%8.7%
FrontierMath22.1%9.6%

Those should represent a floor for the 5.4 variants, assuming OpenAI’s “most capable small models yet” claim holds up. We’ll update this post when third-party benchmarks come in.

Who Should Care

If you’re building agents, Mini is the obvious pick for sub-agent work that still needs real reasoning. Computer use support at $0.75 per million input tokens is a big deal. Previously, you needed the full GPT-5.4 at $2.50 for that capability.

If you’re running high-throughput pipelines, Nano at $0.20 per million input tokens (or $0.10 on batch) handles classification, extraction, and routing at scale. OpenAI’s recommended pattern is to use a larger model as the orchestrator and Nano as the executor.

If you’re on ChatGPT Free or Go, Mini is the best reasoning model you’ve had access to. It won’t match GPT-5.4 on the hardest tasks, but it handles everyday coding and thinking work well enough that the free tier just got meaningfully more useful.

The broader pattern here is clear. OpenAI is filling out the GPT-5.4 lineup the same way they did with GPT-5: flagship first, then Mini and Nano within two weeks. The goal is a model for every price point and every workload, from $180-per-million-token Pro tasks down to five-cent-per-million-token batch classification. Today’s launch fills in the bottom of that range.


Sources: OpenAI GPT-5.4 Mini and Nano announcement, OpenAI API Models documentation, OpenAI API Pricing, Engadget, Inc.com

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