Model profile
openai

OpenAI: GPT-4o

OpenAI: GPT-4o is a budget multimodal generalist from openai with a heavy runtime profile, extended context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalHeavy latencyExtended contextBudget pricing
Intelligence
14.1

Benchmark blend

Coding
N/A

Dev workflow signal

Context
128K Tokens

Extended

Input Price
$0.00

Budget tier

Decision snapshot
45

OpenAI: GPT-4o currently reads as a budget multimodal option with extended context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Multimodal
Latency tier
Heavy
Price tier
Budget
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
14.1
14

General reasoning and benchmark headroom.

Limited
Speed
N/A
46

Latency data is partial.

Situational
Context
128K Tokens
76

How much prompt and task state can stay in view.

Competitive
Price
$0.00
86

$0.00 output / 1M

Efficient

Editorial Profile

OpenAI: GPT-4o in one narrative

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

Use-case specificCoding score 40Math score 80Vision enabled

GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities. For benchmarking against other models, it was briefly called ["im-also-a-good-gpt2-chatbot"](https://twitter.com/LiamFedus/status/1790064963966370209) #multimodal

Identity

openai multimodal profile

Positioning

Long-context research / Multimodal with extended context and heavy runtime.

Cost posture

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

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

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

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

  • 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.

Compare Next

Similar profiles worth opening next

openai

OpenAI: GPT-5.4

Intelligence
57.0
Context
1050K Tokens
Input Price
$2.50
openai

OpenAI: GPT-5.3-Codex

Intelligence
54.0
Context
400K Tokens
Input Price
$1.75
openai

OpenAI: GPT-5.2-Codex

Intelligence
49.0
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
14.1
MMLU Pro
77.3%
GPQA
51.1%
HLE
3.7%
Coding

Software implementation, debugging quality, and coding benchmark signal.

SciCode
33.4%

Extra benchmark cuts are not available for this category yet.

Math

Formal reasoning, structured problem solving, and competition-style math.

AIME
10.3%
Math 500
79.7%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

LCR
53.0%

Extra benchmark cuts are not available for this category yet.

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
128K Tokens
Vision
Enabled
Modalities
text, image, file->text, file
Tokenizer
GPT
Max Completion
16384
Moderation
Yes
Supported Parameters
frequency_penaltylogit_biaslogprobsmax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_logprobstop_pweb_search_options
Input Modalities
textimagefile
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.00
Output
per 1M output tokens
$0.00
Blended
AA 3:1 mix
$0.00

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

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.