Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-5.4 mini (xhigh) | Muse Spark 1.2 (xhigh) |
|---|---|---|
| Input ($/M tokens) | $0.75 | $1.25 |
| Output ($/M tokens) | $4.5 | $4.25 |
Verdict. Muse Spark 1.2 (xhigh) takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.1× the per-million-token cost, Muse Spark 1.2 (xhigh) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Muse Spark 1.2 (xhigh) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-5.4 mini (xhigh) is strongest on Coding Index (56.1), Intelligence Index (40.9). Muse Spark 1.2 (xhigh) leads on Coding Index (72.2), Intelligence Index (56.8).
Speed. Throughput is comparable — 200 tok/s vs 234 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.
Provider. OpenAI and Meta sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Meta 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): GPT-5.4 mini (xhigh) costs $90.00 ($1080/year); Muse Spark 1.2 (xhigh) costs $101.25 ($1215/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.4 mini (xhigh) ≈ $12.75/run, Muse Spark 1.2 (xhigh) ≈ $14.75/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.4 mini (xhigh) ≈ $600/run, Muse Spark 1.2 (xhigh) ≈ $675/run. GPT-5.4 mini (xhigh) 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.
Data from Artificial Analysis API — 12 benchmarks
GPT-5.4 mini (xhigh) is cheaper overall. Its blended price (3:1 input/output ratio) is $1.69/M tokens vs $2.00/M for Muse Spark 1.2 (xhigh).
Muse Spark 1.2 (xhigh) wins 2 out of 12 benchmarks compared to 0 for GPT-5.4 mini (xhigh). See the detailed benchmark chart above for per-category results.
Muse Spark 1.2 (xhigh) generates tokens faster at 234 tok/s vs 200 tok/s. GPT-5.4 mini (xhigh) also has lower time-to-first-token (7.94s vs 15.76s).
Choose based on your priorities: GPT-5.4 mini (xhigh) for lower cost, Muse Spark 1.2 (xhigh) for stronger benchmark performance, and Muse Spark 1.2 (xhigh) for faster generation. For latency-sensitive apps, check the TTFT comparison above.