Quick answer
How do I list the models and check my credit on LLMwithCrypto?
Call GET https://llmwithcrypto.com/api/v1/models for the list of model ids, in the OpenAI format, and GET https://llmwithcrypto.com/api/v1/credits for the credit left in US dollars. Both take your API key as a Bearer token and are free. As of 23 October 2026, LLMwithCrypto serves 12 open-weight models, from DeepSeek V4 Pro to Mistral Small 4.
List the models
GET/api/v1/models
Returns the models your key can call, in the OpenAI list format. The id is the value to send in the model field of a chat completion. The example shows the first four entries; created is illustrative.
Authentication: API key in the Authorization: Bearer API_KEY header.
Response 200
{
"object": "list",
"data": [
{
"id": "deepseek-v4-pro",
"object": "model",
"created": 1792742400,
"owned_by": "deepseek"
},
{
"id": "deepseek-v4.1-flash",
"object": "model",
"created": 1792742400,
"owned_by": "deepseek"
},
{
"id": "deepseek-r1",
"object": "model",
"created": 1792742400,
"owned_by": "deepseek"
},
{
"id": "qwen3.5-397b-a17b",
"object": "model",
"created": 1792742400,
"owned_by": "qwen"
}
]
}Code examples
curl -s "https://llmwithcrypto.com/api/v1/models" \
-H "Authorization: Bearer $LLMWITHCRYPTO_API_KEY"import os
from openai import OpenAI
client = OpenAI(
base_url="https://llmwithcrypto.com/api/v1",
api_key=os.environ["LLMWITHCRYPTO_API_KEY"],
)
for model in client.models.list():
print(model.id, model.owned_by)import OpenAI from 'openai';
const client = new OpenAI({
baseURL: 'https://llmwithcrypto.com/api/v1',
apiKey: process.env.LLMWITHCRYPTO_API_KEY,
});
for await (const model of client.models.list()) console.log(model.id, model.owned_by);Read the credit left
GET/api/v1/credits
Returns the credit on your account in US dollars, as a decimal string so that no precision is lost, and the time it was last updated. Calling it costs nothing. The figures are illustrative.
Authentication: API key in the Authorization: Bearer API_KEY header.
Response 200
{
"object": "credits",
"balance_usd": "41.2731",
"currency": "USD",
"updated_at": "2026-10-23T09:41:07Z"
}Code examples
curl -s "https://llmwithcrypto.com/api/v1/credits" \
-H "Authorization: Bearer $LLMWITHCRYPTO_API_KEY"import os
import requests
resp = requests.get(
"https://llmwithcrypto.com/api/v1/credits",
headers={"Authorization": "Bearer " + os.environ["LLMWITHCRYPTO_API_KEY"]},
timeout=30,
)
resp.raise_for_status()
print("credit left:", resp.json()["balance_usd"], "USD")const res = await fetch('https://llmwithcrypto.com/api/v1/credits', {
headers: { Authorization: `Bearer ${process.env.LLMWITHCRYPTO_API_KEY}` },
});
const credits = await res.json();
console.log('credit left:', credits.balance_usd, 'USD');Which model ids can I use?
The model value, what the model is good for and its context window, as of 23 October 2026. Prices per million tokens are on the pricing page.
| Model id | Model | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
deepseek-v4-pro | DeepSeek V4 Pro | 1M | $1.254 | $3.762 |
deepseek-v4.1-flash | DeepSeek V4.1 Flash | 1M | $0.285 | $1.14 |
deepseek-r1 | DeepSeek R1 | 160K | $0.57 | $2.208 |
qwen3.5-397b-a17b | Qwen3.5 397B A17B | 256K | $0.57 | $3.42 |
qwen3-235b-a22b-instruct-2507 | Qwen3 235B A22B Instruct | 256K | $0.161 | $0.57 |
gpt-oss-120b | gpt-oss-120b | 128K | $0.142 | $0.57 |
gpt-oss-20b | gpt-oss-20b | 128K | $0.033 | $0.161 |
glm-4.7 | GLM-4.7 | 200K | $0.57 | $2.09 |
llama-3.3-70b-instruct | Llama 3.3 70B Instruct | 128K | $0.209 | $0.475 |
gemma-4-31b | Gemma 4 31B | 256K | $0.19 | $0.38 |
mistral-large-3 | Mistral Large 3 | 256K | $0.475 | $1.424 |
mistral-small-4 | Mistral Small 4 | 256K | $0.142 | $0.57 |
Should my app read the model list at start-up?
It is a good habit. Models are added and, more rarely, retired; every change is dated in the changelog. Reading GET https://llmwithcrypto.com/api/v1/models when your app starts lets it check that the id it is configured with still exists, instead of finding out from a 404 model_not_found in production.
The list only holds open-weight models. Only open-weight models whose licences allow serving them as an API: DeepSeek, Qwen, gpt-oss, Mistral, Llama, Gemma and others listed on the models page. We run them on GPUs we rent and operate. Each model keeps its own licence and use policy (for example Meta’s Llama Acceptable Use Policy and the “Built with Llama” notice); using a model through us means accepting them.
How do I avoid running out of credit?
- Read the credit regularly.
GET https://llmwithcrypto.com/api/v1/creditsis free; a check every hour or after each batch is enough for most apps. - Set your own floor. When
balance_usddrops under a level you choose, alert yourself and top up before calls start failing. - Handle
402. A call that the credit cannot pay comes back as402 insufficient_balanceand costs nothing; the errors page shows how to react.
Credit has no expiry date: what you do not spend this month is still there next year, so topping up early costs you nothing.
Models and credits: common questions
Why is GPT or Claude not in the list?
We do not sell access to GPT, Claude, Gemini or Grok: their makers forbid reselling API access without their approval, and we do not have it.
Does the model list show prices?
No, it follows the OpenAI format. Prices per million tokens are on the pricing page and on each model page.
Is the credit shared between my API keys?
Yes. Keys belong to the account and all spend the same credit. Make one API key per app, agent or teammate and revoke any of them from the dashboard without touching the others.