Compare/Muse Spark 1.3 (xhigh) vs o4-mini (high)

Muse Spark 1.3 (xhigh)vso4-mini (high)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Meta

Muse Spark 1.3 (xhigh)

Input
$1.25/M
Output
$4.25/M
Speed
186 tok/s
TTFT
42.55s
OpenAI

o4-mini (high)

Input
$1.1/M
Output
$4.4/M
Speed
145 tok/s
TTFT
22.85s

Winner by Category

Cheaper
o4-mini (high)
Faster (tok/s)
Muse Spark 1.3 (xhigh)
Lower Latency
o4-mini (high)
Benchmarks (2-0)
Muse Spark 1.3 (xhigh)

Pricing Comparison

MetricMuse Spark 1.3 (xhigh)o4-mini (high)
Input ($/M tokens)$1.25$1.1
Output ($/M tokens)$4.25$4.4
Cost for 1M input + 100K output tokens:
Muse Spark 1.3 (xhigh)$1.68
o4-mini (high)$1.54

Speed Comparison

Output Speed (tokens/s) — higher is better
Muse Spark 1.3 (xhigh)
186 tok/s
o4-mini (high)
145 tok/s
Time to First Token (seconds) — lower is better
Muse Spark 1.3 (xhigh)
42.55s
o4-mini (high)
22.85s

Editorial Analysis

Verdict. Muse Spark 1.3 (xhigh) wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.

Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Muse Spark 1.3 (xhigh) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Muse Spark 1.3 (xhigh) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Muse Spark 1.3 (xhigh) is strongest on Coding Index (76.5), Intelligence Index (60.8). o4-mini (high) leads on Intelligence Index (26.1).

Speed. On throughput, Muse Spark 1.3 (xhigh) generates tokens at 186 tok/s versus 145 tok/s — about 22% faster. On time-to-first-token, o4-mini (high) responds in 22850ms vs 42550ms, which matters most for chat-style UIs.

Provider. Meta and OpenAI sell to overlapping but distinct developer audiences: Meta tends to ship frontier reasoning models with premium positioning, while OpenAI often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Muse Spark 1.3 (xhigh) costs $101.25 ($1215/year); o4-mini (high) costs $99.00 ($1188/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Muse Spark 1.3 (xhigh) ≈ $14.75/run, o4-mini (high) ≈ $14.30/run. At agent/realtime scale (200M input / 100M output per million requests): Muse Spark 1.3 (xhigh) ≈ $675/run, o4-mini (high) ≈ $660/run. o4-mini (high) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
60.826.1
Coding Index
76.5
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Muse Spark 1.3 (xhigh)2 wins
0 winso4-mini (high)

Frequently Asked Questions

Which is cheaper, Muse Spark 1.3 (xhigh) or o4-mini (high)?

o4-mini (high) is cheaper overall. Its blended price (3:1 input/output ratio) is $1.93/M tokens vs $2.00/M for Muse Spark 1.3 (xhigh).

Which model performs better on benchmarks?

Muse Spark 1.3 (xhigh) wins 2 out of 12 benchmarks compared to 0 for o4-mini (high). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Muse Spark 1.3 (xhigh) generates tokens faster at 186 tok/s vs 145 tok/s. However, o4-mini (high) has lower time-to-first-token (22.85s vs 42.55s).

When should I use Muse Spark 1.3 (xhigh) vs o4-mini (high)?

Choose based on your priorities: o4-mini (high) for lower cost, Muse Spark 1.3 (xhigh) for stronger benchmark performance, and Muse Spark 1.3 (xhigh) for faster generation. For latency-sensitive apps, check the TTFT comparison above.