Deepseek V4.1 Flash
Quick start
# Inspect the price — a plain request returns the 402 challenge:
curl -i https://api.glianalabs.com/v1/chat/completions \
-H "content-type: application/json" \
-d '{
"model": "@cf/deepseek-ai/deepseek-v4.1-flash-1017",
"messages": [{"role": "user", "content": "<your message>"}]
}'
# Pay + run in one step with the mppx CLI (create a wallet: npx mppx account create):
npx mppx https://api.glianalabs.com/v1/chat/completions \
-J '{"model": "@cf/deepseek-ai/deepseek-v4.1-flash-1017", "messages": [{"role": "user", "content": "<your message>"}]}'Parameters
A list of messages comprising the conversation so far.
Parameters for audio output. Required when modalities includes 'audio'.
Penalizes new tokens based on their existing frequency in the text so far.
Modify the likelihood of specified tokens appearing in the completion. Maps token IDs to bias values from -100 to 100.
Whether to return log probabilities of the output tokens.
An upper bound for the number of tokens that can be generated for a completion.
Deprecated in favor of max_completion_tokens. The maximum number of tokens to generate.
Set of 16 key-value pairs that can be attached to the object.
Output types requested from the model (e.g. ['text'] or ['text', 'audio']).
ID of the model to use (e.g. '@cf/zai-org/glm-4.7-flash, etc').
How many chat completion choices to generate for each input message.
Whether to enable parallel function calling during tool use.
Penalizes new tokens based on whether they appear in the text so far.
Reasoning effort. Supported levels: max, high, low, none. Compatibility aliases: auto maps to high; minimal maps to none; medium maps to high; xhigh maps to max.
How the result is returned (e.g. a URL or base64 data).
If specified, the system will make a best effort to sample deterministically.
Up to 4 sequences where the API will stop generating further tokens.
Whether to store the output for model distillation / evals.
If true, partial message deltas will be sent as server-sent events.
Sampling temperature between 0 and 2.
A list of tools the model may call.
How many top log probabilities to return at each token position (0-20). Requires logprobs=true.
Nucleus sampling: considers the results of the tokens with top_p probability mass.
A unique identifier representing your end-user, for abuse monitoring.
Options for the web search tool (when using built-in web search).