gpt-5-chat

OpenRouter · Chat model

gpt-5-chat is listed here as a chat model from OpenRouter. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Provider and model identifiers are kept in their original form for accuracy.

openrouter-openrouter-openai-gpt-5-chat

Input

$1.2500 / 1M tokens

Output

$10.0000 / 1M tokens

Cached input

$0.1250 / 1M tokens

Context window

16.4K

Catalog generated: Jul 13, 2026

Compare this model Open a side-by-side table using this route and a close match from the current catalog. Estimate cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill.

Quick read

Best for

Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.

Things to verify

Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.

Pricing

Item	Price
Input	$1.2500 / 1M tokens
Output	$10.0000 / 1M tokens
Cached input	$0.1250 / 1M tokens
Embedding	$1.2500 / 1M tokens

Limits

Context window

16.4K

Max input tokens

128.0K

Max output tokens

16.4K

Max tokens

16.4K

Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification. API vs subscription Learn when API pricing matters compared with ChatGPT, Claude Code, Cursor, or Copilot subscriptions. Cache and batch pricing Understand cached input, cache write, batch, priority, and flex pricing rows shown on this page.

Capabilities

Capability	Supported
Vision	-
Function calling	-
Parallel function calling	-
Tool choice	Supported
Prompt caching	-
Reasoning	Supported
Response schema	-
System messages	-
Audio input	-
Audio output	-
Web search	-
PDF input	-
Video input	-

Benchmarks

Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer

Benchmark	Score	Metric	Scope	Checked	Source
SWE-bench Verified	74.9%	accuracy (%)	Base model: gpt-5 (GPT-5 (high))	2026-05-31	Link
Aider Polyglot	88.0%	accuracy (%)	Base model: gpt-5 (GPT-5 (high))	2026-05-31	Link
GPQA Diamond	85.7%	accuracy (%)	Base model: gpt-5 (GPT-5 (high))	2026-05-31	Link
AIME 2025	94.6%	accuracy (%)	Base model: gpt-5 (GPT-5 (high))	2026-05-31	Link
Tau2-bench Telecom	96.7%	accuracy (%)	Base model: gpt-5 (GPT-5 (high))	2026-05-31	Link
Aider Polyglot	88.0%	percent correct	Base model: GPT-5 (openai/gpt-5)	2026-05-31	Link
Aider Polyglot	86.7%	percent correct	Base model: GPT-5 (openai/gpt-5)	2026-05-31	Link
Aider Polyglot	81.3%	percent correct	Base model: GPT-5 (openai/gpt-5)	2026-05-31	Link

Sources

Source links	LiteLLM repository LiteLLM model cost map
Pricing data	LiteLLM model cost map
Synced at	2026-05-28
Catalog generated	2026-07-13T14:21:55.110Z