Model profile
OpenAI

OpenAI: GPT-4

OpenAI: GPT-4 is a premium-priced text-first model from OpenAI with partial runtime data, compact context posture, and the clearest fit around agent workflows / long-context research.

Best for: Agent workflows / Long-context researchN/A latencyCompact contextPremium pricing
Intelligence
6.8

Benchmark blend

Coding
13.1

Dev workflow signal

Context
8K Tokens

Compact

Input Price
$30.00

Premium tier

Decision snapshot
14

OpenAI: GPT-4 currently reads as a premium text-first option with compact context and a partially published runtime profile.

Overall profile
Use-case specific
Best for
Agent workflows / Long-context research
Latency tier
N/A
Price tier
Premium
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
6.8
7

General reasoning and benchmark headroom.

Limited
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
8K Tokens
28

How much prompt and task state can stay in view.

Limited
Price
$30.00
18

$60.00 output / 1M

Premium

Editorial Profile

OpenAI: GPT-4 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 13Math score 57

OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous models due to its broader general knowledge and advanced reasoning...

Identity

OpenAI text-first profile

Positioning

Agent workflows / Long-context research with compact context and partially published runtime.

Cost posture

Premium spend profile. Best when the upside justifies tighter budget control.

Strengths
  • The available source data suggests a balanced profile rather than one dominant edge.

Tradeoffs
  • Pricing sits in premium territory, so bulk usage needs tighter cost controls.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

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

  • Context window is more comfortable for focused tasks than extremely long sessions.

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

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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
6.8
MMLU Pro
56.2%
GPQA
34.9%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
13.1

Extra benchmark cuts are not available for this category yet.

Math

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

Math 500
56.8%

Extra benchmark cuts are not available for this category yet.

Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
33.2%

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
8K Tokens
Vision
Text-first
Modalities
text
Tokenizer
GPT
Max Completion
4096
Moderation
No
Supported Parameters
frequency_penaltylogit_biaslogprobsmax_completion_tokensmax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_logprobstop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$30.00
Output
per 1M output tokens
$60.00
Blended
AA 3:1 mix
$37.50

This model trades into premium territory. It makes sense when capability upside matters more than raw volume efficiency.

Metadata

Raw source tables at the end

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