1. Create an API key
Create or sign in to your IteraCompute account, then create a key in the Console.
Integration guideOpenAI-compatibleUse a model with LiteLLM through IteraCompute.
Route requests through one interface.
Connect in three steps
2. Configure the base URL
Set api_base and use openai/ before the API Model ID. This prefix is LiteLLM routing metadata.
3. Select the model
Use the exact API Model ID for your chosen model. Check its context and capabilities before enabling agent or vision features.
Choose your model
Example configuration
Keep API keys in your server environment or tool credential store. Replace the example key field with your own key where applicable.
OpenAI-compatible API
import os
from litellm import completion
response = completion(
model="openai/qwen/qwen3.8-27b",
api_base="https://api.iteracompute.com/v1",
api_key=os.environ["ITERACOMPUTE_API_KEY"],
messages=[{"role": "user", "content": "Hello!"}],
max_tokens=512,
extra_body={"chat_template_kwargs": {"enable_thinking": False}},
)
print(response.choices[0].message.content)model_list:
- model_name: itera-model
litellm_params:
model: openai/qwen/qwen3.8-27b
api_base: https://api.iteracompute.com/v1
api_key: os.environ/ITERACOMPUTE_API_KEYVersion and verification
Configuration reference · reviewed 2026-10-15. A reproducible end-to-end tool test has not been recorded here. Record your installed version and test date when running the steps below.
Success criterion
Run completion and, if used, the proxy route. Check a non-empty content field and confirm the intended upstream model.
Record the installed version
python -m pip show litellmTest the configured tool itself after the API check below. An HTTP 200 or a cURL result alone does not verify that tool.
Test the connection
cURL · Chat Completions
# Bash / zsh / WSL; set ITERACOMPUTE_API_KEY in your environment first.
curl --fail-with-body https://api.iteracompute.com/v1/chat/completions \
-H "Authorization: Bearer $ITERACOMPUTE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qwen/qwen3.8-27b","messages":[{"role":"user","content":"Reply with exactly: Hello!"}],"max_tokens":512}'Check that choices[0].message.content contains visible text; HTTP 200 alone is insufficient. Reasoning may consume the output budget. For free Qwen, use the first free call example to disable thinking, then send a prompt inside your tool.
Selected model capabilities
These are API capabilities of the selected model. Feature availability in your workflow also depends on the tool and its settings; reasoning controls vary by model.
- Chat CompletionsSupported
- Tool callingSupported
- ReasoningSupported
- Image inputSupported
- StreamingSupported
Troubleshooting
Provider not recognized
Use openai/qwen/qwen3.8-27b for LiteLLM routing and api_base=https://api.iteracompute.com/v1. The openai/ prefix is routing metadata, not part of the API model ID.
Proxy model not found
The client calls the model_name from your proxy configuration; litellm_params.model contains the provider-prefixed upstream model. Check which name you are sending.
Key or response missing
Set the key in the LiteLLM process, including the proxy process when used. Confirm choices[0].message.content has text before testing routing or fallback policies.
429 / Request limits
Check account-wide monthly usage and TPM. Honor Retry-After and avoid parallel retries. Free Qwen has no automatic paid overage; other models use their published prices.
401 / 403: check the key and model permission. Free Qwen requires no balance or card. For paid models, also check available balance.
Start building with LiteLLM.
Connect your key, choose a model and send your first request.