Meta: Muse Spark 1.1 by Meta AI — Pricing, Benchmarks &amp; Real Outputs

Alternatives to Meta: Muse Spark 1.1

Meta: Muse Spark 1.1 is good. These would like a word anyway.

Meta: Muse Spark 1.1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

Updated Jul 16, 2026

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Compare Meta: Muse Spark 1.1

Alternatives to Meta: Muse Spark 1.1

Meta: Muse Spark 1.1 is good. These would like a word anyway.

Meta: Muse Spark 1.1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

Updated Jul 16, 2026

Share

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 window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates or as a subagent, and generalizes zero-shot to new tools, MCP servers, and custom skills. It supports structured output, parallel function calling, built-in search with citations, and configurable reasoning effort.

Provider

Release Date

2026-07-09

Size

LARGE

Pricing

In: $1.25/1M

Out: $4.25/1M

Rival’s tab

$1.02

58/58 receipts survived

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"meta/muse-spark-1.1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Deep analysisPsychometrics, taste index, writing DNA

Writing DNA

Stylometric Fingerprint

Based on 29 text responses

Tick = global average

Vocabulary Diversity61%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length19.9 words

Average words per sentence.

Hedging0.10

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting3.7

**Bold** markers per 1,000 characters.

List Usage2.0

Bullet and numbered list items per 1,000 characters.

Section Structure0.52

Markdown headings per 1,000 characters.

Emoji Usage0.01

Emoji per 1,000 characters.

Transitions0.02

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

80%

Across 29 responses

Favorites

Movie

The Shawshank Redemption

City

Kyoto

Game

Minecraft

Sponsored

Model Responses

53 outputs · $1.00 tracked across 53 receipts

Related Models

Llama 4 Behemoth

Llama 4 Behemoth is Meta's most powerful model yet with 288B active parameters and 16 experts (nearly 2T total parameters), outperforming GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on several STEM benchmarks.

Llama 4 Maverick

Llama 4 Maverick is Meta's multimodal expert model with 17B active parameters and 128 experts (400B total parameters). It outperforms GPT-4o and Gemini 2.0 Flash across various benchmarks, achieving an ELO of 1417 on LMArena. Designed for sophisticated AI applications with excellent image understanding and creative writing.

Llama 4 Scout

Llama 4 Scout is Meta's compact yet powerful multimodal model with 17B active parameters and 16 experts (109B total parameters). It fits on a single H100 GPU with Int4 quantization and offers an industry-leading 10M token context window, outperforming Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 across various benchmarks.

Llama 3.1 70B (Instruct)

Llama 3.1 70B offers a dramatically expanded context window and improved performance on mathematical reasoning and general knowledge tasks.

Llama 3.1 405B

Llama 3.1 405B is Meta's most powerful open-source model, outperforming even proprietary models on various benchmarks.

Llama 3 70B

Llama 3 70B is a large language model from Meta with strong performance and efficiency for real-time interactions.

Keep exploring

Meta: Muse Spark 1.1 vs MiniMax M3

Real outputs compared side by side

Best AI for Complex Reasoning

Which AI reasons best under pressure? Ranked across 11 challenges: contracts,...

Loading...

Compare Meta: Muse Spark 1.1

Alternatives to Meta: Muse Spark 1.1

Meta: Muse Spark 1.1 is good. These would like a word anyway.

Meta: Muse Spark 1.1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

Updated Jul 16, 2026

Share

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 window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates or as a subagent, and generalizes zero-shot to new tools, MCP servers, and custom skills. It supports structured output, parallel function calling, built-in search with citations, and configurable reasoning effort.

Provider

Release Date

2026-07-09

Size

LARGE

Pricing

In: $1.25/1M

Out: $4.25/1M

Rival’s tab

$1.02

58/58 receipts survived

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"meta/muse-spark-1.1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Deep analysisPsychometrics, taste index, writing DNA

Writing DNA

Stylometric Fingerprint

Based on 29 text responses

Tick = global average

Vocabulary Diversity61%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length19.9 words

Average words per sentence.

Hedging0.10

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting3.7

**Bold** markers per 1,000 characters.

List Usage2.0

Bullet and numbered list items per 1,000 characters.

Section Structure0.52

Markdown headings per 1,000 characters.

Emoji Usage0.01

Emoji per 1,000 characters.

Transitions0.02

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

80%

Across 29 responses

Favorites

Movie

The Shawshank Redemption

City

Kyoto

Game

Minecraft

Sponsored

Model Responses

53 outputs · $1.00 tracked across 53 receipts

Related Models

Llama 4 Behemoth

Llama 4 Behemoth is Meta's most powerful model yet with 288B active parameters and 16 experts (nearly 2T total parameters), outperforming GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on several STEM benchmarks.

Llama 4 Maverick

Llama 4 Maverick is Meta's multimodal expert model with 17B active parameters and 128 experts (400B total parameters). It outperforms GPT-4o and Gemini 2.0 Flash across various benchmarks, achieving an ELO of 1417 on LMArena. Designed for sophisticated AI applications with excellent image understanding and creative writing.

Llama 4 Scout

Llama 4 Scout is Meta's compact yet powerful multimodal model with 17B active parameters and 16 experts (109B total parameters). It fits on a single H100 GPU with Int4 quantization and offers an industry-leading 10M token context window, outperforming Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 across various benchmarks.

Llama 3.1 70B (Instruct)

Llama 3.1 70B offers a dramatically expanded context window and improved performance on mathematical reasoning and general knowledge tasks.

Llama 3.1 405B

Llama 3.1 405B is Meta's most powerful open-source model, outperforming even proprietary models on various benchmarks.

Llama 3 70B

Llama 3 70B is a large language model from Meta with strong performance and efficiency for real-time interactions.

Keep exploring

Meta: Muse Spark 1.1 vs MiniMax M3

Real outputs compared side by side

Best AI for Complex Reasoning

Which AI reasons best under pressure? Ranked across 11 challenges: contracts,...

Loading...

Compare Meta: Muse Spark 1.1

Alternatives to Meta: Muse Spark 1.1

Meta: Muse Spark 1.1 is good. These would like a word anyway.

Meta: Muse Spark 1.1 has opinions about your brand too.Ask 10 models what they tell people about you. Verbatim receipts.Run the mirror

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 window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates or as a subagent, and generalizes zero-shot to new tools, MCP servers, and custom skills. It supports structured output, parallel function calling, built-in search with citations, and configurable reasoning effort.

Provider

Release Date

2026-07-09

Size

LARGE

Pricing

In: $1.25/1M

Out: $4.25/1M

Rival’s tab

$1.02

58/58 receipts survived

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"meta/muse-spark-1.1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Deep analysisPsychometrics, taste index, writing DNA

Writing DNA

Stylometric Fingerprint

Based on 29 text responses

Tick = global average

Vocabulary Diversity61%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length19.9 words

Average words per sentence.

Hedging0.10

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting3.7

**Bold** markers per 1,000 characters.

List Usage2.0

Bullet and numbered list items per 1,000 characters.

Section Structure0.52

Markdown headings per 1,000 characters.

Emoji Usage0.01

Emoji per 1,000 characters.

Transitions0.02

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

80%

Across 29 responses

Favorites

Movie

The Shawshank Redemption

City

Kyoto

Game

Minecraft

Sponsored

Model Responses

53 outputs · $1.00 tracked across 53 receipts

Related Models

Llama 4 Behemoth

Llama 4 Behemoth is Meta's most powerful model yet with 288B active parameters and 16 experts (nearly 2T total parameters), outperforming GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on several STEM benchmarks.

Llama 4 Maverick

Llama 4 Maverick is Meta's multimodal expert model with 17B active parameters and 128 experts (400B total parameters). It outperforms GPT-4o and Gemini 2.0 Flash across various benchmarks, achieving an ELO of 1417 on LMArena. Designed for sophisticated AI applications with excellent image understanding and creative writing.

Llama 4 Scout

Llama 4 Scout is Meta's compact yet powerful multimodal model with 17B active parameters and 16 experts (109B total parameters). It fits on a single H100 GPU with Int4 quantization and offers an industry-leading 10M token context window, outperforming Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 across various benchmarks.

Llama 3.1 70B (Instruct)

Llama 3.1 70B offers a dramatically expanded context window and improved performance on mathematical reasoning and general knowledge tasks.

Llama 3.1 405B

Llama 3.1 405B is Meta's most powerful open-source model, outperforming even proprietary models on various benchmarks.

Llama 3 70B

Llama 3 70B is a large language model from Meta with strong performance and efficiency for real-time interactions.

Keep exploring

Meta: Muse Spark 1.1 vs MiniMax M3

Real outputs compared side by side

Best AI for Complex Reasoning

Which AI reasons best under pressure? Ranked across 11 challenges: contracts,...

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 window. The model is designed to orchestrate multi-agent workflows, acting as either a main agent that plans and delegates or as a subagent, and generalizes zero-shot to new tools, MCP servers, and custom skills. It supports structured output, parallel function calling, built-in search with citations, and configurable reasoning effort.

Provider

Release Date

2026-07-09

Size

LARGE

Pricing

In: $1.25/1M

Out: $4.25/1M

Rival’s tab

$1.02

58/58 receipts survived

Get API accessProvider and language code samples

Provider

fromimport openai  OpenAI

client = OpenAI(
"https://openrouter.ai/api/v1"    base_url=,
"$OPENROUTER_API_KEY"    api_key=,
)

response = client.chat.completions.create(
"meta/muse-spark-1.1"    model=,
"role""user""content""Hello!"    messages=[{: , : }],
)
print(response.choices[0].message.content)

Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.

Deep analysisPsychometrics, taste index, writing DNA

Writing DNA

Stylometric Fingerprint

Based on 29 text responses

Tick = global average

Vocabulary Diversity61%

Unique words vs. total words. Higher = richer vocabulary.

Sentence Length19.9 words

Average words per sentence.

Hedging0.10

"Might", "perhaps", "arguably" per 100 words.

Bold Formatting3.7

**Bold** markers per 1,000 characters.

List Usage2.0

Bullet and numbered list items per 1,000 characters.

Section Structure0.52

Markdown headings per 1,000 characters.

Emoji Usage0.01

Emoji per 1,000 characters.

Transitions0.02

"However", "moreover", "furthermore" per 100 words.

Opening Habits

Consistency

80%

Across 29 responses

Favorites

Movie

The Shawshank Redemption

City

Kyoto

Game

Minecraft

Sponsored

Model Responses

53 outputs · $1.00 tracked across 53 receipts

Related Models

Llama 4 Behemoth

Llama 4 Behemoth is Meta's most powerful model yet with 288B active parameters and 16 experts (nearly 2T total parameters), outperforming GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on several STEM benchmarks.

Llama 4 Maverick

Llama 4 Maverick is Meta's multimodal expert model with 17B active parameters and 128 experts (400B total parameters). It outperforms GPT-4o and Gemini 2.0 Flash across various benchmarks, achieving an ELO of 1417 on LMArena. Designed for sophisticated AI applications with excellent image understanding and creative writing.

Llama 4 Scout

Llama 4 Scout is Meta's compact yet powerful multimodal model with 17B active parameters and 16 experts (109B total parameters). It fits on a single H100 GPU with Int4 quantization and offers an industry-leading 10M token context window, outperforming Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 across various benchmarks.

Llama 3.1 70B (Instruct)

Llama 3.1 70B offers a dramatically expanded context window and improved performance on mathematical reasoning and general knowledge tasks.

Llama 3.1 405B

Llama 3.1 405B is Meta's most powerful open-source model, outperforming even proprietary models on various benchmarks.

Llama 3 70B

Llama 3 70B is a large language model from Meta with strong performance and efficiency for real-time interactions.

Keep exploring

Meta: Muse Spark 1.1 vs MiniMax M3

Real outputs compared side by side