/v1/classifier
Score a batch of typed questions against one shared context in a single non-streaming call.
/v1/classifier
Send one shared context (either messages or state) plus a batch of typed questions, and receive one answer per question ID. It is built for classification and extraction: labeling, support scoring, moderation, and guardrails.
The endpoint is also available as POST /v1/systemone, POST /v1/decisions, and POST /models/:owner/:model/v1/classifier, where the model is taken from the URL path.
HTTP request
POST https://api.featherless.ai/v1/classifier
Authenticate with Authorization: Bearer <FEATHERLESS_API_KEY> and send a JSON body. The maximum request body is 50 MiB.
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Classifier Playground
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Supported models
We are bringing up open-weight models for the classifier endpoint. These are the ones supported today:
| Model | Input / 1M tokens | Output / 1M tokens |
|---|---|---|
| featherless-ai/Qwen3.6-35B-A3B-classifier | $0.28 | $0 |
| featherless-ai/Qwen3.8-27B-classifier | $0.3 | $0 |
| featherless-ai/gemma-4-26B-A4B-classifier | $0.28 | $0 |
| featherless-ai/RWKV-small-classifier | $0.03 | $0 |
| featherless-ai/RWKV-mid-classifier | $0.1 | $0 |
| featherless-ai/RWKV-std-classifier | $0.2 | $0 |
| featherless-ai/Qwen3.5-4B-classifier | $0.03 | $0 |
| featherless-ai/gemma-4-12B-it-classifier | $0.24 | $0 |
Filter the full catalog on the models page: https://featherless.ai/models?modalities=classifier
Request body
Provide exactly one of messages or state, plus a nonempty questions object. Each key in questions becomes a key in the answers you get back.
{
"model": "featherless-ai/Qwen3.6-35B-A3B-classifier",
"messages": [
{ "role": "user", "content": "Review: \"The red bicycle arrived early and my dog Pip loves it.\"" }
],
"questions": {
"sentiment": {
"type": "choice",
"instructions": "Overall sentiment of the review.",
"criteria": {
"positive": "Clearly favorable",
"negative": "Clearly unfavorable"
}
},
"quality": {
"type": "score",
"instructions": "Rate the writing quality.",
"criteria": ["Very poor", "Poor", "Fair", "Good", "Excellent"]
},
"mentions_dog": {
"type": "noul",
"instructions": "Does the review mention a dog?",
"criteria": { "true": "Mentions a dog", "false": "No dog mentioned" }
}
}
}Question types
choice: criteria is an object with 2 to 50 named options; the answer returns the chosen key plus a probability per option.score: criteria is an ordered array of 2 to 50 level descriptions, lowest to highest; the answer returns a numeric score, per-level probabilities, and a legend.noul: criteria may describe the true and false options; the answer returns a single scalar in the range 0.01 to 0.99.
Question objects are strict: unknown keys are rejected rather than ignored. The optional options object accepts score_format, raw_logits, choice_mode, and score_mode. Completion parameters such as temperature or max_tokens are accepted for client compatibility and ignored; the classifier is always non-streaming.
Response body
The response contains one answer per question ID. The model field is always the canonical platform model name, not the string echoed from the request. usage.cost is the settled charge for the request in USD, omitted on subscription plans.
{
"model": "featherless-ai/Qwen3.6-35B-A3B-classifier",
"answers": {
"sentiment": {
"type": "choice",
"choice": "positive",
"confidence": 0.94,
"probabilities": { "positive": 0.94, "negative": 0.06 }
},
"quality": {
"type": "score",
"score": 4,
"confidence": 0.81,
"probabilities": { "0": 0.01, "1": 0.02, "2": 0.05, "3": 0.11, "4": 0.81 },
"legend": { "0": "Very poor", "1": "Poor", "2": "Fair", "3": "Good", "4": "Excellent" }
},
"mentions_dog": { "type": "noul", "noul": 0.97 }
},
"usage": { "input_tokens": 407, "output_tokens": 3, "cost": 0.000004 }
}Errors
Validation failures return 422 with the standard error envelope, including a details array of the failing fields. Requesting a model that is not enabled for the classifier returns 404.
Example
curl --fail-with-body https://api.featherless.ai/v1/classifier \
--header "Authorization: Bearer $FEATHERLESS_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "featherless-ai/Qwen3.6-35B-A3B-classifier",
"messages": [{ "role": "user", "content": "Review: The red bicycle arrived early and my dog Pip loves it." }],
"questions": {
"sentiment": {
"type": "choice",
"instructions": "Overall sentiment of the review.",
"criteria": { "positive": "Clearly favorable", "negative": "Clearly unfavorable" }
}
}
}'