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Model profile
openai

OpenAI: GPT-4 Turbo Preview

OpenAI: GPT-4 Turbo Preview is a premium text-first model from openai with a heavy runtime profile, extended context posture, and the clearest fit around long-context research / reasoning.

Best for: Long-context research / ReasoningHeavy latencyExtended contextPremium pricing
Intelligence
N/A

Benchmark blend

Coding
N/A

Dev workflow signal

Context
128K Tokens

Extended

Input Price
$10.00

Premium tier

Decision snapshot
48

OpenAI: GPT-4 Turbo Preview currently reads as a premium text-first option with extended context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Reasoning
Latency tier
Heavy
Price tier
Premium
Source coverage
OpenRouter
Compare this modelSee leaderboard

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
N/A
44

General reasoning and benchmark headroom.

Situational
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
$10.00
38

$30.00 output / 1M

Expensive

Editorial Profile

OpenAI: GPT-4 Turbo Preview 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 36

The preview GPT-4 model with improved instruction following, JSON mode, reproducible outputs, parallel function calling, and more. Training data: up to Dec 2023. **Note:** heavily rate limited by OpenAI while in preview.

Identity

openai text-first profile

Positioning

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

Cost posture

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

Strengths

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

Tradeoffs

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

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

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

Best fit

  • 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.

No benchmark data is available for this model 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
Text-first
Modalities
text->text, text
Tokenizer
GPT
Max Completion
4096
Moderation
Yes
Supported Parameters
frequency_penaltylogit_biaslogprobsmax_tokenspresence_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_logprobstop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$10.00
Output
per 1M output tokens
$30.00
Blended
AA 3:1 mix
N/A

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.