Last refreshed 2026-10-19. Next refresh: weekly.
Why use Muse Spark 1.2 Contributor on Vercel AI Gateway?
Vercel AI Gateway offers Muse Spark 1.2 Contributor with pay-as-you-go pricing at $0.10/1M input tokens. Vercel AI Gateway is a unified AI proxy providing a single OpenAI-compatible API endpoint to 275+ models from 25+ providers including Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, xAI, Alibaba, Amazon, ByteDance, Cohere, MiniMax, MoonshotAI, KwaiPilot, Black Forest Labs, Recraft, Voyage AI, NVIDIA, and more.
Compare Muse Spark 1.2 Contributor across 3 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport AI_GATEWAY_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],meta/muse-spark-1.2-contributorRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],
base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
model="meta/muse-spark-1.2-contributor",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "meta/muse-spark-1.2-contributor", not the LLMReference slug "muse-spark-1.2-contributor".
- creator/model-name e.g. kwaipilot/kat-coder-pro-v2
- The examples expect AI_GATEWAY_API_KEY; rename it only if your application config maps the new variable.
Compare Muse Spark 1.2 Contributor Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Meta Model API | $0.10 | $0.20 |
| Vercel AI Gateway | $0.10 | $0.20 |
| OpenRouter | $0.10 | $0.20 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.10 |
| Output tokens | $0.20 |
Capabilities
About Muse Spark 1.2 Contributor
Muse Spark 1.2 Contributor is the Contributor-tier Model API id (muse-spark-1.2-contributor) for Muse Spark 1.2. Distinct catalog ID (same pattern as muse-spark-1.3-contributor). 1,048,576-token context; multimodal inputs. Contributor mode: discounted tokens in exchange for permission to use content to train future Meta models. FP pricing: $0.10/$0.20 per 1M in/out (cached input $0.002).