ChatGPT Down? Here Are Open LLM API Alternatives

TL;DR: When ChatGPT is down, your workflow doesn't have to stop. TokShop offers OpenAI-compatible, pay-as-you-go access to open models like DeepSeek V3.2, GLM 4.6, Kimi K2, and Qwen3 Coder — so you can switch your API calls in minutes without rewriting code.

Why "ChatGPT Down" Matters for Developers

If you're searching "chatgpt down," you're likely hitting an outage right now — either in the ChatGPT web app or the API. Recent reports indicate OpenAI has even slowed development of advanced models following a security incident, which means reliability concerns aren't just about uptime; they're about strategic dependence on a single vendor.

The practical fix is redundancy. By pointing your existing OpenAI SDK calls at a compatible endpoint like TokShop's https://tokshop.xyz/v1, you can route traffic to open models that aren't affected by ChatGPT's infrastructure issues. This isn't about replacing ChatGPT permanently — it's about having a working fallback when you need it.

How to Switch from ChatGPT API to Open Models in Minutes

Because TokShop uses the OpenAI API format, you don't need new SDKs or complex integrations. The change is a matter of swapping the base URL and API key.

Step 1: Get a key. Sign up at https://tokshop.xyz/register, create an API key (looks like sk-tok-...), and add prepaid USD credits.

Step 2: Update your client. Here's a minimal Python example using the openai library:

from openai import OpenAI

client = OpenAI(
    base_url="https://tokshop.xyz/v1",
    api_key="sk-tok-your-key-here"
)

response = client.chat.completions.create(
    model="deepseek-v3.2",  # or glm-4.6, kimi-k2, qwen3-coder
    messages=[{"role": "user", "content": "Explain rate limiting simply."}]
)

print(response.choices[0].message.content)

Step 3: Verify usage. Every call is logged with token counts and exact USD cost in your dashboard, so you can track spend immediately.

Which Open Model Should You Use as a Backup?

The right fallback depends on your workload. Here's a direct comparison of the models available on TokShop, with prices per million tokens:

Model	Context Length	Input Price	Output Price	Best For
DeepSeek V3.2	128,000	$0.42	$0.63	Cost-sensitive, high-volume tasks
GLM 4.6	200,000	$0.90	$3.30	Long documents, balanced quality
Kimi K2	131,072	$0.855	$3.45	General chat, creative writing
Qwen3 Coder	262,144	$2.25	$11.25	Code generation, large codebases

For most production use, DeepSeek V3.2 is the pragmatic choice — it's dramatically cheaper than ChatGPT's typical pricing, making it viable for bulk processing even when ChatGPT is online. If you're working with very long inputs (like entire code repositories), Qwen3 Coder's 262K context window is the standout, though you'll pay a premium for it.

What About Reliability During Outages?

No API is immune to outages, but open-model providers offer different failure modes than a single centralized service. Since TokShop routes to multiple open models, you can implement a simple retry-and-fallback pattern: try ChatGPT first, and if it fails, automatically retry on DeepSeek or GLM.

A basic approach in Python:

def chat_with_fallback(prompt):
    try:
        return call_openai(prompt)  # your existing code
    except Exception:
        fallback_client = OpenAI(
            base_url="https://tokshop.xyz/v1",
            api_key="sk-tok-fallback-key"
        )
        return fallback_client.chat.completions.create(
            model="glm-4.6",
            messages=[{"role": "user", "content": prompt}]
        ).choices[0].message.content

This pattern turns a "ChatGPT down" incident from a production blocker into a minor blip. You can also check TokShop's pricing page to estimate fallback costs before committing.

How Do Costs Compare to ChatGPT?

Open models are significantly cheaper than proprietary APIs, which is part of why they're attractive as backups. At current TokShop rates, processing 1 million input tokens on DeepSeek V3.2 costs $0.42 — a fraction of what comparable GPT-4-class models charge.

Pricing is prepaid, so you control spend. If your credits run out, the API returns HTTP 402 (insufficient_balance) rather than silently failing, which makes cost monitoring straightforward. For detailed integration guidance, the TokShop docs cover authentication and model parameters.

FAQ

Can I use my existing OpenAI SDK code with TokShop?

Yes. TokShop's API is OpenAI-compatible, so you only need to change the base_url to https://tokshop.xyz/v1 and use your TokShop API key. No other code changes are required.

What happens if I run out of credits during an outage?

You'll receive an HTTP 402 error with insufficient_balance. The API doesn't cut you off mid-request; it returns a clear error so you can top up credits and retry.

Which model is best for code generation when ChatGPT is down?

Qwen3 Coder offers the largest context window (262,144 tokens) and is optimized for coding tasks, making it the strongest fallback for large codebases. For smaller tasks, DeepSeek V3.2 is a cost-effective alternative.