--- title: Meta: Muse Spark 1.1 API | Text Generation | ModelsLab description: Build with Meta: Muse Spark 1.1 API by Meta. Text generation, chat, code, and reasoning. Pay-per-use. Free tier. url: https://modelslab.com/models/meta/meta-muse-spark-1.1.md canonical: https://modelslab.com/models/meta/meta-muse-spark-1.1 type: product component: Playground/LLM/Index generated_at: 2026-07-19T10:03:24.497786Z --- Meta: Muse Spark 1.1 --- [LLMs.txt](https://modelslab.com/models/meta/meta-muse-spark-1.1/llms.txt) [.md](https://modelslab.com/models/meta/meta-muse-spark-1.1.md) Meta: Muse Spark 1.1 --- Choose a prompt below to get started or type your own message Explain quantum computing in simple terms Write a Python function to sort a list Create a marketing email for a SaaS product Compare REST vs GraphQL APIs Send ### Meta: Muse Spark 1.1 meta meta-muse-spark-1.1 Copy model ID PricingInput $1.25 / 1M tokens Output $4.25 / 1M tokens API EndpointsOpenAI Compatible `https://modelslab.com/api/v7/llm/chat/completions`Endpoint Anthropic Compatible `https://modelslab.com/api/v7/llm/v1/messages`Messages `https://modelslab.com/api/v7/llm/v1/messages/count_tokens`Count Tokens `https://modelslab.com/api/v7/llm/v1/models`Models Use with Claude Code cURL Example ParametersSystem MessageYou are a helpful AI assistant specialized in providing accurate and detailed responses. Temperature0.7 Max Tokens1000 Top P0.9 Frequency Penalty0 Presence Penalty0 Model Info Support Related Models --- Discover similar models you might be interested in [View all LLM Models](https://modelslab.com/models?feature=llmaster) [#### mistralai/Mistral: Mistral Nemo mistralai-mistral-nemo From $0.02/M tokens](https://modelslab.com/models/mistralai/mistralai-mistral-nemo) [#### openai/OpenAI: GPT-4o (2024-08-06) openai-gpt-4o-2024-08-06 From $6.25/M tokens](https://modelslab.com/models/openai/openai-gpt-4o-2024-08-06) [#### openai/OpenAI: gpt-oss-safeguard-20b openai-gpt-oss-safeguard-20b From $0.19/M tokens](https://modelslab.com/models/openai/openai-gpt-oss-safeguard-20b) [#### anthropic/Anthropic: Claude Opus Latest anthropic-claude-opus-latest From $15.00/M tokens](https://modelslab.com/models/anthropic/anthropic-claude-opus-latest) [#### mistralai/Mistral: Mistral Small 3 mistralai-mistral-small-24b-instruct-2501 From $0.07/M tokens](https://modelslab.com/models/mistralai/mistralai-mistral-small-24b-instruct-2501) [#### qwen/Qwen: Qwen Plus 0728 (thinking) qwen-qwen-plus-2025-07-28-thinking From $0.52/M tokens](https://modelslab.com/models/qwen/qwen-qwen-plus-2025-07-28-thinking) [#### openai/OpenAI: GPT-4o (2024-11-20) openai-gpt-4o-2024-11-20 From $6.25/M tokens](https://modelslab.com/models/openai/openai-gpt-4o-2024-11-20) [#### qwen/Qwen: Qwen3 30B A3B qwen-qwen3-30b-a3b From $0.33/M tokens](https://modelslab.com/models/qwen/qwen-qwen3-30b-a3b) [#### nousresearch/Nous Hermes 2 Mixtral 8X7B Dpo NousResearch-Nous-Hermes-2-Mixtral-8x7B-DPO From $0.60/M tokens](https://modelslab.com/models/nousresearch/NousResearch-Nous-Hermes-2-Mixtral-8x7B-DPO) [#### cohere/Cohere: Command R7B (12-2024) cohere-command-r7b-12-2024 From $0.09/M tokens](https://modelslab.com/models/cohere/cohere-command-r7b-12-2024) [#### refuel\_ai/Refuel LLM V2 togethercomputer-Refuel-Llm-V2 From $0.72/M tokens](https://modelslab.com/models/refuel_ai/togethercomputer-Refuel-Llm-V2) [#### google/Gemma 3N E4B Instruct google-gemma-3n-E4B-it From $0.09/M tokens](https://modelslab.com/models/google/google-gemma-3n-E4B-it) [#### z-ai/Z.ai: GLM 4.6 z-ai-glm-4.6 From $1.25/M tokens](https://modelslab.com/models/z-ai/z-ai-glm-4.6) [#### mistralai/Mistral: Codestral 2508 mistralai-codestral-2508 From $0.60/M tokens](https://modelslab.com/models/mistralai/mistralai-codestral-2508) [#### anthropic/Anthropic Claude Sonnet Latest anthropic-claude-sonnet-latest From $6.00/M tokens](https://modelslab.com/models/anthropic/anthropic-claude-sonnet-latest) [#### qwen/Qwen2.5 Coder 32B Instruct qwen-qwen-2.5-coder-32b-instruct From $0.83/M tokens](https://modelslab.com/models/qwen/qwen-qwen-2.5-coder-32b-instruct) [#### mistralai/Mistral: Ministral 3 3B 2512 mistralai-ministral-3b-2512 From $0.10/M tokens](https://modelslab.com/models/mistralai/mistralai-ministral-3b-2512) [#### alibaba\_cloud/Qwen: Qwen3.5-27B qwen-qwen3.5-27b From $1.35/M tokens](https://modelslab.com/models/alibaba_cloud/qwen-qwen3.5-27b) Open Source Alternatives --- Explore open-source models that offer similar capabilities with full transparency and flexibility [View all open source models](https://modelslab.com/models?feature=llm&provider=open-source-models) [MU Popular](https://modelslab.com/models/modelslab/uncensored-chat)[ModelsLab](https://modelslab.com/models/modelslab) [Modelslab: Uncensored Chat Open Source Model](https://modelslab.com/models/modelslab/uncensored-chat) About Meta: Muse Spark 1.1 --- Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context... ### Technical Specifications Model IDmeta-muse-spark-1.1 CategoryLLM Models TaskText Generation Price$2.75 per million tokens AddedJuly 16, 2026 ### Key Features - Chat completion and multi-turn conversation API - Streaming response with token-by-token output - Function calling and tool use support - System prompts and role-based messaging - JSON mode and structured output ### Quick Start Integrate Meta: Muse Spark 1.1 into your application with a single API call. Get your API key from the [pricing page](https://modelslab.com/pricing) to get started. PythonJavaScriptcURLPHP ``` import requests import json url = "https://modelslab.com/api/v7/llm/chat/completions" headers = { "Content-Type": "application/json" } data = { "model_id": "meta-muse-spark-1.1", "messages": [ { "role": "user", "content": "Hello!" } ], "max_tokens": 1000, "key": "YOUR_API_KEY" } try: response = requests.post(url, headers=headers, json=data) response.raise_for_status() # Raises an HTTPError for bad responses (4XX or 5XX) result = response.json() print("API Response:") print(json.dumps(result, indent=2)) except requests.exceptions.HTTPError as http_err: print(f"HTTP error occurred: {http_err} - {response.text}") except Exception as err: print(f"Other error occurred: {err}") ``` ### Pricing Meta: Muse Spark 1.1 API costs $2.750000 per million tokens. Pay only for what you use with no minimum commitments. [View pricing plans](https://modelslab.com/pricing) ### Use Cases - AI chatbots and virtual assistants - Code generation and developer tools - Content writing and copywriting automation - Data analysis, summarization, and extraction [Browse LLM Models](https://modelslab.com/models?feature=llmaster) [More from Meta](https://modelslab.com/models/open_router) [View Pricing](https://modelslab.com/pricing) Meta: Muse Spark 1.1 FAQ --- ### What is Meta: Muse Spark 1.1? Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context... ### How do I use the Meta: Muse Spark 1.1 API? You can integrate Meta: Muse Spark 1.1 into your application with a single API call. Sign up on ModelsLab to get your API key, then use the model ID "meta-muse-spark-1.1" in your API requests. We provide SDKs for Python, JavaScript, and cURL examples in the API documentation. ### How much does Meta: Muse Spark 1.1 cost? Meta: Muse Spark 1.1 costs $2.750000 per million tokens. ModelsLab uses pay-per-use pricing with no minimum commitments. A free tier is available to get started. ### What is the Meta: Muse Spark 1.1 model ID? The model ID for Meta: Muse Spark 1.1 is "meta-muse-spark-1.1". Use this ID in your API requests to specify this model. ### Does Meta: Muse Spark 1.1 have a free tier? Yes, ModelsLab offers a free tier that lets you try Meta: Muse Spark 1.1 and other AI models. Sign up to get free API credits and start building immediately. --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-07-19*