Model profile
openai
New in 2026

OpenAI: GPT-5.4

OpenAI: GPT-5.4 is a mid-range multimodal generalist from openai with a heavy runtime profile, large context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsHeavy latencyLarge contextMid-range pricing
Intelligence
57.0

Benchmark blend

Coding
57.3

Dev workflow signal

Context
1050K Tokens

Large

Input Price
$2.50

Mid-range tier

Decision snapshot
59

OpenAI: GPT-5.4 currently reads as a mid-range multimodal option with large context and a heavy runtime profile.

Overall profile
Selective fit
Best for
Long-context research / Agent workflows
Latency tier
Heavy
Price tier
Mid-range
Source coverage
OpenRouterArtificial AnalysisVision signal

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
57.0
57

General reasoning and benchmark headroom.

Situational
Speed
77 tok/s
27

TTFT 179.20s

Limited
Context
1050K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$2.50
62

$15.00 output / 1M

Competitive

Editorial Profile

OpenAI: GPT-5.4 in one narrative

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

Selective fitCoding score 57Math score 36Vision enabled

GPT-5.4 is OpenAI’s latest frontier model, unifying the Codex and GPT lines into a single system. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs, enabling high-context reasoning, coding, and multimodal analysis within the same workflow. The model delivers improved performance in coding, document understanding, tool use, and instruction following. It is designed as a strong default for both general-purpose tasks and software engineering, capable of generating production-quality code, synthesizing information across multiple sources, and executing complex multi-step workflows with fewer iterations and greater token efficiency.

Identity

openai multimodal profile

Positioning

Long-context research / Agent workflows with large context and heavy runtime.

Cost posture

Balanced spend profile. Easier to justify in mixed production and exploration workloads.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Costs look manageable, but still deserve attention in always-on agents or batch jobs.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

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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
57.0
GPQA
92.0%
HLE
41.6%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
57.3
SciCode
56.6%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
73.9%
TAU2
91.5%
TerminalBench Hard
57.6%
LCR
74.0%

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
1050K Tokens
Vision
Enabled
Modalities
text, image, file->text, file
Tokenizer
GPT
Max Completion
128000
Moderation
Yes
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokenspresence_penaltyreasoningresponse_formatseedstopstructured_outputstool_choicetoolstop_logprobs
Input Modalities
textimagefile
Output Modalities
text
Price architecture
Input
per 1M input tokens
$2.50
Output
per 1M output tokens
$15.00
Blended
AA 3:1 mix
$5.63

This model sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.

OR Web Search Price
$0.0100
OR Cache Read
$0.00

Metadata

Raw source tables at the end

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