Model profile
OpenAI
New in 2026

GPT-5.4 nano (xhigh)

GPT-5.4 nano (xhigh) is a budget-priced text-first model from OpenAI with balanced runtime profile, partial context coverage, and the clearest fit around agent workflows / reasoning.

Best for: Agent workflows / ReasoningBalanced latencyN/A contextBudget pricing
Intelligence
44.0

Benchmark blend

Coding
43.9

Dev workflow signal

Context
N/A

N/A

Input Price
$0.20

Budget tier

Decision snapshot
57

GPT-5.4 nano (xhigh) currently reads as a budget text-first option with partially published context and a balanced runtime profile.

Overall profile
Selective fit
Best for
Agent workflows / Reasoning
Latency tier
Balanced
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
44.0
44

General reasoning and benchmark headroom.

Situational
Speed
153 tok/s
68

TTFT 2.69s

Competitive
Context
N/A
N/A

How much prompt and task state can stay in view.

Unavailable
Price
$0.20
86

$1.25 output / 1M

Efficient

Editorial Profile

GPT-5.4 nano (xhigh) in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Selective fitCoding score 44Math score N/A

The GPT-5.4 nano (xhigh) AI model by OpenAI.

Identity

OpenAI text-first profile

Positioning

Agent workflows / Reasoning with partially published context and balanced runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Latency and throughput look responsive enough for interactive loops.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency is balanced rather than ultra-fast, which is fine for most workflows but not the snappiest tier.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context limits are only partially published, so long-session planning needs extra validation.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

Explore Next

Similar profiles worth opening next

OpenAI

OpenAI: GPT-5.4

Intelligence
56.8
Context
1050K Tokens
Input Price
$2.50
OpenAI

OpenAI: GPT-5.3-Codex

Intelligence
53.6
Context
400K Tokens
Input Price
$1.75
OpenAI

OpenAI: GPT-5.2

Intelligence
51.3
Context
400K Tokens
Input Price
$1.75

Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
44.0
GPQA
81.7%
HLE
26.5%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
43.9
SciCode
46.9%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
75.9%
TAU2
76.0%
TerminalBench Hard
42.4%
LCR
66.0%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$0.20
Output
per 1M output tokens
$1.25
Blended
AA 3:1 mix
$0.46

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.