GPT-5

Azure OpenAI chat

GPT-5 is an Azure OpenAI chat model.It supports a 272,000-token context windowwith up to 128,000 output tokens.Input is priced at $1.25/M tokens and output at $10.00/M tokens. Capabilities include function calling, vision, reasoning, prompt caching. Route GPT-5 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: May 12, 2026 View source ↗
Cost calculator

Estimate GPT-5 spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
0272,000
400
0128,000
5,000
01,000,000
cached @ $0.1250/M
Per request
$0.007750
in $0.003750 · out $0.004000
Per day
$38.75
5,000 requests
Per month
$1,179
152,188 requests

Estimate uses $1.25/M input · $10.00/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.

Input $1.25/M
Output $10.00/M
Cached input $0.125/M

Limits

Context window
272,000 tokens
Max input
272,000 tokens
Max output
128,000 tokens
Modalities
vision, pdf, text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls ✓ supported
  • Vision input ✓ supported
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input ✓ supported
  • Streaming ✓ supported
  • Structured output ✓ supported
  • Prompt caching ✓ supported
  • Reasoning ✓ supported

Where it's strong

  • +pricing — cheaper than 79% of priced chat models on Future AGI
  • +long-context tasks — context window in the top 15% of peers
  • +PDF input — only 16% of chat models on Future AGI advertise this
  • +parallel tool calls — only 21% of chat models on Future AGI advertise this
  • +prompt caching — only 23% of chat models on Future AGI advertise this

Watch out for

  • No major caveats flagged from public spec.

Benchmark scores

Reported public benchmark numbers. Each row links to the source.

MATH-500math· 0-shot
Captured May 12, 2026
AIME 2024math· 0-shot
Captured May 12, 2026
BFCL v3agent· multi-turn
Captured May 12, 2026
HumanEvalcode· 0-shot
Captured May 12, 2026
IFEvalgeneral· 0-shot
Captured May 12, 2026
AIME 2025math· 0-shot
Captured May 12, 2026
Chatbot Arena ELOgeneral· overall
Captured May 12, 2026
LiveCodeBenchcode· pass@1
Captured May 12, 2026
MMLU-Proreasoning· 0-shot
Captured May 12, 2026
Aider Polyglotcode· pass@1
Captured May 12, 2026
GPQA Diamondreasoning· 0-shot
Captured May 12, 2026
MMMUmultimodal· 0-shot
Captured May 12, 2026
SWE-bench Verifiedagent· agentic
Captured May 12, 2026
Humanity's Last Examreasoning· 0-shot
Captured May 12, 2026
ARC-AGI-2reasoning· 0-shot
Captured May 12, 2026
Try it

Call GPT-5 via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# GPT-5 via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="azure-openai/gpt-5",
    messages=[{"role": "user", "content": "Hello, GPT-5!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="azure-openai/gpt-5",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗
Advanced: fallback + cache config (YAML)
strategy: cost-optimized
targets:
  - model: gpt-5
    provider: azure-openai
    weight: 80
fallbacks:
  - model: claude-opus-4-6
    provider: azure-ai-foundry
  - model: claude-opus-4-6-20260205
    provider: anthropic
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Same model on other providers

gpt-5 is also available via 2 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
OpenAI$1.25/M$10.00/MMay 12, 2026
GitHub CopilotMay 12, 2026

Compare with similar models

Grouped by Chatbot Arena tier (GPT-5 sits at 1450 ELO).

FAQ

How much does GPT-5 cost?

Input is priced at $1.25 per 1M tokens and output at $10.00 per 1M tokens (Azure OpenAI, last verified May 12, 2026).

What is the context window of GPT-5?

GPT-5 supports a 272,000-token context window with up to 128,000 output tokens.

Does GPT-5 support function calling?

Yes — GPT-5 supports function (tool) calling, including parallel tool calls.

Is GPT-5 good for production?

GPT-5 is well-suited for pricing — cheaper than 79% of priced chat models on Future AGI and long-context tasks — context window in the top 15% of peers.

How can I route to GPT-5 with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for GPT-5

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.