Muse Spark 1.2 (xhigh) logo
Meta
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Proprietary model

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Released August 2026

Muse Spark 1.2 (xhigh) API Provider Benchmarking & Analysis

Model Comparison

Analysis of API providers for Muse Spark 1.2 (xhigh) across performance metrics including latency (time to first token), output speed (output tokens per second), price and others. API providers benchmarked include Meta.

Fastest

Output speed

Total 1 provider

Lowest Latency

Time to first answer token

Total 1 provider

Lowest Price

#1
MetaMeta
$0.78

Blended price (per 1M tokens)

Total 1 provider

Muse Spark 1.2 (xhigh) is available through Meta.

Benchmarks of providers are not available for this model.
Please see the models page for Muse Spark 1.2 (xhigh) for details of the model and its intelligence compared to other models.

Highlights

Speed

Output tokens per second · Higher is better
No data available

End-to-End Response Time

Seconds · Lower is better
No data available

Price

USD per 1M tokens (blended) · Lower is better

Update: Default performance benchmarking workload has updated to 10k input tokens to better reflect production use cases. You can still select different workloads above.

Pricing

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens) · Lower is better · 10,000 input tokens

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Pricing: Blended Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended) · Lower is better

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Pricing: Cache Discount

1 - (cache hit price / input price) · Higher is better

Reduction in input token cost due to cache hit relative to input price. Formula: 1 - (Cache Hit Price per Token / Input Token Price), where cache hit price is the first-party cache hit price or the median provider cache hit price. Note that this discount figure does not account for all costs associated with cache hits, such as cache write and storage costs.

Output Speed vs. Price

Blended at 7:2:1 (cache-input-output) · Output speed: output tokens per second · USD per 1M tokens (blended)
Most attractive quadrant
No data available

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Speed

Measured by Output Speed (tokens per second)

Output Speed: Muse Spark 1.2 (xhigh)

Output speed: output tokens per second · 10,000 input tokens
No data available

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Latency vs. Output Speed

Latency: seconds to first token received · Output speed: output tokens per second · 10,000 input tokens
Most attractive quadrant
No data available

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Latency

Measured by Time (seconds) to First Token

Time to First Answer Token

Seconds to first token received · Lower is better · 10,000 input tokens
No data available

Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

End-to-End Response Time

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time

Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · 10,000 input tokens
No data available

Seconds to receive a 500 token response. Key components:

  • Input time: Time to receive the first response token
  • Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
  • Answer time: Time to generate 500 output tokens, based on output speed

Key Comparison Metrics & API Features

Meta logoMeta
1.05M
Proprietary
$0.40
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Frequently Asked Questions

Common questions about Muse Spark 1.2 (xhigh) providers

Muse Spark 1.2 (xhigh) is available through 1 API provider: Meta. Each provider offers different performance characteristics and pricing.

Muse Spark 1.2 (xhigh) is currently available through 1 API provider that we benchmark and track.

The most affordable provider for Muse Spark 1.2 (xhigh) by blended price is Meta ($0.78 per 1M tokens). Blended price uses a 7:2:1 cache hit/input/output token ratio.

The provider with the lowest input token pricing for Muse Spark 1.2 (xhigh) is Meta ($1.25 per 1M input tokens).

The provider with the lowest output token pricing for Muse Spark 1.2 (xhigh) is Meta ($4.25 per 1M output tokens).

The only provider of Muse Spark 1.2 (xhigh) supports JSON mode for structured output.

The only provider of Muse Spark 1.2 (xhigh) supports function calling (tool use).

When choosing a provider for Muse Spark 1.2 (xhigh), consider: output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and API features like JSON mode or function calling.

Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.

For information about Muse Spark 1.2 (xhigh)'s intelligence, capabilities, modalities, and how it compares to other models, see the model overview page. View model overview