Proxies for ChatGPT and the OpenAI Chat API

Why proxy ChatGPT / OpenAI API traffic

Three AI workloads regularly benefit from proxy routing against the OpenAI API surface:

1. Regional content-policy evaluation. OpenAI applies regional variation to certain content categories. Measuring the delta between ChatGPT responses from US, UK, DE, FR, JP, and other origins is methodology — not bypass. Residentials anchored to each target country give the authentic origin needed for the eval to mean anything.

2. Multi-turn agent evaluation. Agent benchmarks running 20-50 turns per session need stable IP through the conversation. Residential rotation breaks session cookies; ISP static keeps the conversation coherent. Our LLM evaluation use case covers the methodology.

3. API-rate-limit distribution for eval workloads. Running a 500-prompt eval across 10 origin countries = 5,000 calls. Distributing across exits while respecting OpenAI's per-key rate limits needs careful per-origin concurrency management.

What this page isn't

• Not a way to access ChatGPT in countries where OpenAI has restricted access. SquadProxy's AUP doesn't support circumvention of provider-level geographic restrictions.
• Not a way to bypass rate limits on a single account. Rate limits are per-account regardless of the proxy in front.
• Not for generating content that violates OpenAI's Usage Policies.

Recommended configuration

For a typical regional-eval pipeline against the OpenAI Chat Completions API:

import httpx

PROXY = "http://USER:PASS@gateway.squadproxy.com:7777"

def eval_chat(prompt: str, country: str, model: str = "gpt-4o"):
    return httpx.post(
        "https://api.openai.com/v1/chat/completions",
        json={"model": model, "messages": [{"role": "user", "content": prompt}]},
        headers={
            "Authorization": f"Bearer {OPENAI_API_KEY}",
            "X-Squad-Class": "residential",
            "X-Squad-Country": country,
            "X-Squad-Session": "per-request",
        },
        proxies=PROXY,
        timeout=120,
    ).json()

For multi-turn agent eval, swap X-Squad-Class to isp and X-Squad-Session to sticky-10m for session continuity.

Regional eval reference set

Ten countries with good coverage for OpenAI regional evaluation:

• US: baseline, OpenAI's primary inference region
• GB: EU-adjacent, English-working, distinct content policy
• DE: largest EU economy, EU AI Act baseline
• FR: CNIL-aligned eval anchor, French-language testing
• JP: APAC baseline, Japanese-language testing
• KR: APAC APAC-secondary, Korean-language
• SG: APAC hub, multilingual
• CA: bilingual (EN + Quebec French), NA-secondary
• AU: Pacific / APAC south
• NL: EU northwest, multilingual

See residential proxy page for pool depth per country and multilingual benchmark methodology for the reproducibility framing.

Plans that fit

• Solo ($149/mo) covers a single researcher running evaluation scripts and one-off prompt probes — 50 GB residential handles ~100k eval calls.
• Team ($699/mo) covers startups and mid-size labs with continuous eval pipelines — 500 GB residential + 1000 concurrent.
• Lab ($2,999/mo) covers continuous evaluation fleets and safety red-team coordination — 2 TB residential + 3000 concurrent + priority routing.

See pricing for full details.

Related

• LLM evaluation use case
• Multilingual benchmark post
• Safety red-team use case
• Claude API landing
• Gemini API landing