Claude Fable 5 vs Muse Spark 1.1
Head-to-head specifications
| Metric | Claude Fable 5 | Muse Spark 1.1 | Difference |
|---|---|---|---|
| Intelligence Index | 60.0 | 51.0 | +17.6% |
| Coding Index | 76.5 | 71.3 | +7.3% |
| Agentic Index | 52.8 | 37.5 | — |
| Context window | 1M tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $1.68 | $0.62 | +171.0% |
| Output speed (tokens/s) | 65 | 118 | -44.9% |
| Access | Proprietary API | Proprietary API | — |
- Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 51.0).
- Muse Spark 1.1 is the cheaper model to run at $0.62/1M blended tokens — about 2.7× cheaper.
Verdict: Claude Fable 5 or Muse Spark 1.1?
Claude Fable 5 advantages
- General intelligence (+15%)
- Coding ability (+7%)
- Agentic task performance (+29%)
Muse Spark 1.1 advantages
- Affordability (+63%)
- Output speed (+45%)
Which should you choose?
- Choose the Claude Fable 5 if you need the strongest overall reasoning and accuracy.
- Choose the Muse Spark 1.1 if you want the lowest cost per token at scale.
- Choose the Claude Fable 5 if coding and software development are your main workload.
Value for money
Muse Spark 1.1 offers more intelligence per dollar (2.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Claude Fable 5 vs Muse Spark 1.1: which should you choose?
Claude Fable 5 — Anthropic multimodal model with an Intelligence Index of 60, a 1M-token context window and a blended price of $1.68/1M 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.
Claude Fable 5 vs Muse Spark 1.1: Claude Fable 5 scores higher on the Intelligence Index. Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 51.0). Muse Spark 1.1 is the cheaper model to run at $0.62/1M blended tokens — about 2.7× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the Claude Fable 5 scores 60.0 versus 51.0. For software development, the Coding Index puts Claude Fable 5 ahead (76.5 vs 71.3). On agentic, multi-step tool-use tasks, Claude Fable 5 measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Claude Fable 5 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, Muse Spark 1.1 generates faster (118 vs 65 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 $1.68 per 1M tokens). Claude Fable 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 Claude Fable 5 better than the Muse Spark 1.1?
Claude Fable 5 takes the overall edge, though Muse Spark 1.1 wins in specific areas worth weighing. Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 51.0).
What is the main difference between the Claude Fable 5 and the Muse Spark 1.1?
Claude Fable 5 leads overall capability (Intelligence Index 60.0 vs 51.0). Muse Spark 1.1 is the cheaper model to run at $0.62/1M blended tokens — about 2.7× cheaper.
Which is better value?
Muse Spark 1.1 offers more intelligence per dollar (2.3× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the Claude Fable 5 if you need the strongest overall reasoning and accuracy. Choose the Muse Spark 1.1 if you want the lowest cost per token at scale.
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.