CorX Labs

GPT-5 nano

by OpenAI · United States
ProprietaryReasoningVisionTool callingMixture of experts400K context

The smallest GPT-5, priced for classification, extraction and routing rather than open-ended reasoning.


Specification

The numbers

Maker
OpenAI
Released
2025-08
Parameters
Not reported
Architecture
MoE
Context window
400,000 tokens
Max output
128,000 tokens
Input
Text, Image
Output
Text
Reasoning
Yes
Tool calling
Yes
Knowledge cutoff
2024-05
Licence
Proprietary
Availability
Not reported
Weights
Not released

Cost

Price per million tokens

Input
$0.05 / M tokens
Output
$0.40 / M tokens
Cached input
$0.0050
Blended 3:1
$0.138

Standard first-party API rate, excluding batch discounts. Reasoning models bill thinking tokens as output, so cost per answer can far exceed the cost per token suggests.

Published scores

Benchmarks

Figures published by OpenAI or taken from a public leaderboard. Row last checked 2026-08.

GPT-5 nano by capability category, with its rank among models reporting the same tests.
CategoryScore Rank
ReasoningGPQA Diamond71.2%31 of 83 reporting the same tests
MathsAIME 202585.2%27 of 56 reporting the same tests
CodingWriting and repairing real codeNot reported
KnowledgeBreadth of factual recall under exam conditionsNot reported
MultimodalReading charts, diagrams and photographsNot reported
Instruction followingObeying an exact, checkable formatNot reported
Human preferenceWhich answer people pick, blindNot reported

A category averages every benchmark in it that GPT-5 nano reports. The rank counts only models that report the same tests, so it never compares an average over three benchmarks against an average over one.

Every reported test

MMLU-ProKnowledgeNot reportedNo figure published
GPQA DiamondReasoning71.2%Rank 31 of 83 models reporting
AIME 2025Maths85.2%Rank 27 of 56 models reporting
MATH-500MathsNot reportedNo figure published
SWE-bench VerifiedCodingNot reportedNo figure published
SWE-bench ProCodingNot reportedNo figure published
Terminal-Bench 2.1CodingNot reportedNo figure published
Frontier-Bench v0.1ReasoningNot reportedNo figure published
Terminal-Bench 4.0CodingNot reportedNo figure published
LiveCodeBenchCodingNot reportedNo figure published
HumanEvalCodingNot reportedNo figure published
MMMUMultimodalNot reportedNo figure published
IFEvalInstruction followingNot reportedNo figure published
LMArena EloHuman preferenceNot reportedNo figure published

Where these numbers come from

Every score on this page is a published figure, taken from the model's own card, system card, technical report or release post, or from a public leaderboard. CorX Labs did not run these evaluations. Most are self-reported by the lab that built the model, which means they were produced under that lab's own choice of prompt, scaffold and number of attempts — so treat them as a starting point for a shortlist, not as a settled ranking.

A score someone other than the model's maker measured is marked Independent and names its measurer. Those are the stronger numbers on this page — an outside harness has no reason to flatter anyone — and there are not many of them.

Where a figure has not been published, the cell reads Not reported rather than an estimate. Nothing here is inferred, interpolated or guessed. Each model records the month its row was last checked. Full method and caveats.

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