Grok 4.5 vs Muse Spark 1.1
Head-to-head specifications
| Metric | Grok 4.5 | Muse Spark 1.1 | Difference |
|---|---|---|---|
| Intelligence Index | 54.0 | 51.0 | +5.9% |
| Coding Index | 72.4 | 71.3 | +1.5% |
| Agentic Index | 45.7 | 37.5 | — |
| Context window | 922K tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $0.87 | $0.62 | +40.3% |
| Output speed (tokens/s) | 118 | 118 | — |
| Access | Proprietary API | Proprietary API | — |
- Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 51.0).
- Muse Spark 1.1 is the cheaper model to run at $0.62/1M blended tokens — about 1.4× cheaper.
- Muse Spark 1.1 offers the larger context window (1M tokens), useful for long documents and codebases.
Verdict: Grok 4.5 or Muse Spark 1.1?
Grok 4.5 advantages
- General intelligence (+6%)
- Agentic task performance (+18%)
Muse Spark 1.1 advantages
- Context window (+8%)
- Affordability (+29%)
Which should you choose?
- Choose the Grok 4.5 if you need the strongest overall reasoning and accuracy.
- Choose the Muse Spark 1.1 if you work with long documents or large codebases.
- Choose the Grok 4.5 if you build agents or multi-step tool-use workflows.
Value for money
Muse Spark 1.1 offers more intelligence per dollar (1.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Grok 4.5 vs Muse Spark 1.1: which should you choose?
Grok 4.5 — xAI multimodal model with an Intelligence Index of 54, a 922K-token context window and a blended price of $0.87/1M tokens.
Muse Spark 1.1 — Muse multimodal model with an Intelligence Index of 51, a 1M-token context window and a blended price of $0.62/1M tokens.
Grok 4.5 vs Muse Spark 1.1: Grok 4.5 scores higher on the Intelligence Index. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 51.0). Muse Spark 1.1 is the cheaper model to run at $0.62/1M blended tokens — about 1.4× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Grok 4.5 scores 54.0 versus 51.0. For software development, the Coding Index puts Grok 4.5 ahead (72.4 vs 71.3). On agentic, multi-step tool-use tasks, Grok 4.5 measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Muse Spark 1.1 accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, Grok 4.5 generates faster (118 vs 118 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, Muse Spark 1.1 is the cheaper model to run ($0.62 vs $0.87 per 1M tokens). Grok 4.5 is proprietary api and Muse Spark 1.1 is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Grok 4.5 better than the Muse Spark 1.1?
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 51.0).
What is the main difference between the Grok 4.5 and the Muse Spark 1.1?
Grok 4.5 leads overall capability (Intelligence Index 54.0 vs 51.0). Muse Spark 1.1 is the cheaper model to run at $0.62/1M blended tokens — about 1.4× cheaper.
Which is better value?
Muse Spark 1.1 offers more intelligence per dollar (1.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the Grok 4.5 if you need the strongest overall reasoning and accuracy. Choose the Muse Spark 1.1 if you work with long documents or large codebases.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.