DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh): The Ultimate Performance & Pricing Comparison
Deep dive into reasoning, benchmarks, and latency insights.
The Final Verdict in the DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh) Showdown
The current catalog does not contain complete performance evidence for both models, so this page does not declare an overall winner. Use the available fields as comparison signals and validate the models on your own workload.
Model Snapshot
Key decision metrics at a glance.
Machine-readable comparison data
| Model | Metric | Value | Unit | Source / snapshot |
|---|---|---|---|---|
| DeepSeek V4 Pro (Non-reasoning) | Reasoning | 6.0 | benchmark or capability score | Artificial Analysis · current catalog |
| Muse Spark 1.2 (xhigh) | Reasoning | 6.0 | benchmark or capability score | Artificial Analysis · current catalog |
| DeepSeek V4 Pro (Non-reasoning) | Coding | 6.0 | benchmark or capability score | Artificial Analysis · current catalog |
| Muse Spark 1.2 (xhigh) | Coding | 7.0 | benchmark or capability score | Artificial Analysis · current catalog |
| DeepSeek V4 Pro (Non-reasoning) | Multimodal | 3.0 | benchmark or capability score | Artificial Analysis · current catalog |
| Muse Spark 1.2 (xhigh) | Multimodal | 5.0 | benchmark or capability score | Artificial Analysis · current catalog |
| DeepSeek V4 Pro (Non-reasoning) | Long Context | 4.0 | benchmark or capability score | Artificial Analysis · current catalog |
| Muse Spark 1.2 (xhigh) | Long Context | 7.0 | benchmark or capability score | Artificial Analysis · current catalog |
| DeepSeek V4 Pro (Non-reasoning) | Blended Price / 1M tokens | $0.544 | USD per 1M tokens | Artificial Analysis · current catalog |
| Muse Spark 1.2 (xhigh) | Blended Price / 1M tokens | $2 | USD per 1M tokens | Artificial Analysis · current catalog |
| DeepSeek V4 Pro (Non-reasoning) | P95 Latency | — | milliseconds | Artificial Analysis · current catalog |
| Muse Spark 1.2 (xhigh) | P95 Latency | — | milliseconds | Artificial Analysis · current catalog |
| DeepSeek V4 Pro (Non-reasoning) | Tokens per second | 63.061 | tokens per second | Artificial Analysis · current catalog |
| Muse Spark 1.2 (xhigh) | Tokens per second | 0 | tokens per second | Artificial Analysis · current catalog |
Data provided by Artificial Analysis; live values use the current catalog.
Overall Capabilities
This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `DeepSeek V4 Pro (Non-reasoning)` vs `Muse Spark 1.2 (xhigh)`.
Benchmark Breakdown
This grouped bar chart provides a side-by-side comparison for each benchmark metric.
Speed & Latency
Lower time to first token is better; higher tokens per second is better.
The Economics of DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh)
Pricing Breakdown
Compare input and output pricing in USD per 1M tokens.
Real-World Cost Scenario
Per run: 1M input tokens + 250k output tokensDeepSeek V4 Pro (Non-reasoning)$0.652
Muse Spark 1.2 (xhigh)$2.313
DeepSeek V4 Pro (Non-reasoning) costs $1.66 less per run
Your Questions about the DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh) Comparison
Is `DeepSeek V4 Pro (Non-reasoning)` a direct replacement for `Muse Spark 1.2 (xhigh)`?
The current DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh) data does not establish a universal replacement. Compare the available metrics, then validate quality, latency, reliability, and cost on your own workload.
For coding, which is better in the `DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh)` debate?
The current catalog does not contain comparable coding benchmark values for both models, so this page does not declare a coding winner.
How was this `DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh)` comparison conducted?
Our DeepSeek V4 Pro (Non-reasoning) vs Muse Spark 1.2 (xhigh) comparison uses published benchmark, pricing, speed, and latency fields provided by Artificial Analysis. Missing values remain unavailable, and the result should be checked against your workload.