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Core.Today
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Billing note Prompts and responses sent to this model may be used by Meta for model training. Use muse-spark-1.3 for anything personal, confidential or customer-owned. Reasoning model: keep max_tokens >= 2048 (400 ended with empty content in testing).
MetaMediumUltra

Muse Spark 1.3 Contributor

The discounted Contributor tier of Meta's Muse Spark 1.3 - same model, about 1/12 of the standard price, on the condition that prompts and responses may be used by Meta to train its models. Do not send personal, confidential or customer data. Shares an upstream limit of 100 requests / 3M tokens per minute.

186/372credits
input / output ยท per 1M tokens
Same Muse Spark 1.3 model at about 1/12 of the standard price
Prompts and responses may be used for Meta training (the discount condition)
1M-token context, multimodal input (text, image, video, audio, PDF)
Shared upstream limit: 100 RPM / 3M TPM
OpenAI-compatible API via /llm/meta/v1

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Model Specifications

Context Window
1.0M
tokens
Max Output
33K
tokens
Training Cutoff
Not published
Compatible SDK
OpenAI

Capabilities

Vision
Function Calling
Streaming
JSON Mode
System Prompt

Token Pricing (per 1M tokens)

Token TypeCreditsUSD Equivalent
Input Tokens186$0.12
Output Tokens372$0.25
Cached Tokens3.716$0.00

* 1,500 credits โ‰ˆ $1 (actual charges may vary based on usage)

Quick Start

curl -X POST "https://api.core.today/llm/meta/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "muse-spark-1.3-contributor",
  "messages": [
    {
      "role": "user",
      "content": "Summarize this public press release in 3 bullets: ..."
    }
  ],
  "max_tokens": 4096
}'

Parameters

ParameterTypeRequiredDefaultDescription
messagesarrayYes-Chat messages in OpenAI format. Content may be used by Meta for training - no personal or confidential data.
max_tokensintegerNo2048Maximum completion tokens including reasoning. Keep >= 2048 or the answer may be cut off before any content is produced.
temperaturenumberNo0.7Sampling temperature (0-2).
streambooleanNofalseStream the response as server-sent events.

Examples

Low-cost batch summarization

Summarize a public article - content may be used for Meta training.

curl -X POST "https://api.core.today/llm/meta/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer cdt_your_api_key" \
  -d '{
  "model": "muse-spark-1.3-contributor",
  "messages": [
    {
      "role": "user",
      "content": "Summarize this public press release in 3 bullets: ..."
    }
  ],
  "max_tokens": 4096
}'

Tips & Best Practices

1Only send data you are allowed to share for training; otherwise use muse-spark-1.3
2Keep max_tokens >= 2048: reasoning tokens come first and are billed at the output rate
3The 100 RPM / 3M TPM upstream limit is shared across all callers - expect provider_rate_limited under load
4Works with the OpenAI SDK - set base_url to https://api.core.today/llm/meta/v1

Use Cases

Bulk processing of public or synthetic data where cost matters most
Evaluation and prompt iteration with non-sensitive inputs
Internal tooling over open documents