GPT-4o
GitHub Copilot chatGPT-4o is a GitHub Copilot chat model.It supports a 64,000-token context windowwith up to 4,096 output tokens. Capabilities include function calling, vision. Route GPT-4o via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.
We don't have verified per-token pricing for GPT-4o yet. If you have a source from GitHub Copilot's documentation, help us add it — your submission gets reviewed within 48 hours.
Pricing
Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.
| Input | — | |
| Output | — |
Limits
- Context window
- 64,000 tokens
- Max input
- 64,000 tokens
- Max output
- 4,096 tokens
- Modalities
- vision, text
Capabilities
- Function calling ✓ supported
- Parallel tool calls ✓ supported
- Vision input ✓ supported
- Audio input — not advertised
- Audio output — not advertised
- PDF input — not advertised
- Streaming ✓ supported
- Structured output — not advertised
- Prompt caching — not advertised
- Reasoning — not advertised
Where it's strong
- +parallel tool calls — only 21% of chat models on Future AGI advertise this
Watch out for
- !strict structured output — no JSON-schema enforcement, expect retry loops
Benchmark scores
Reported public benchmark numbers. Each row links to the source. Faded bar shows 6-peer average for context.
Call GPT-4o 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.
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-4o 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="github-copilot/gpt-4o",
messages=[{"role": "user", "content": "Hello, GPT-4o!"}],
)
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="github-copilot/gpt-4o",
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"))AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗Advanced: fallback + cache config (YAML) ▸
strategy: cost-optimized
targets:
- model: gpt-4o
provider: github-copilot
weight: 80
fallbacks:
- model: gpt-5-nano
provider: azure-openai
- model: deepseek-v3
provider: azure-ai-foundry
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }Same model on other providers
gpt-4o is also available via 2 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.
| Provider | Input / 1M | Output / 1M | Verified |
|---|---|---|---|
| Azure OpenAI | $2.50/M | $10.00/M | May 12, 2026 |
| OpenAI | $2.50/M | $10.00/M | May 12, 2026 |
Compare with similar models
Grouped by Chatbot Arena tier (GPT-4o sits at 1265 ELO).
≥30 ELO higher
- Claude Opus 4.6Azure AI Foundry · $5.00/M in · $25.00/M out · 200,000 ctx
- Claude Opus 4.6 (2026-02-05)Anthropic · $5.00/M in · $25.00/M out · 1,000,000 ctx
- Gemini 3.1 Pro previewGoogle Vertex AI · $2.00/M in · $12.00/M out · 1,048,576 ctx
- Claude Opus 4.7Azure AI Foundry · $5.00/M in · $25.00/M out · 200,000 ctx
FAQ
How much does GPT-4o cost?
Public per-token pricing for GPT-4o is not yet published. Submit a source on this page to help us add it.
What is the context window of GPT-4o?
GPT-4o supports a 64,000-token context window with up to 4,096 output tokens.
Does GPT-4o support function calling?
Yes — GPT-4o supports function (tool) calling, including parallel tool calls.
Is GPT-4o good for production?
GPT-4o is well-suited for parallel tool calls — only 21% of chat models on Future AGI advertise this. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.
How can I route to GPT-4o 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-4o
Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.
Third-party evals — verify the marketing.
Cross-check our number against the rest of the ecosystem.