AI Agent StoreReasoning
Muse Spark 1.3 leads by 0.4 points.
Can it work through constraints and connect clues? LiveBench uses spatial, navigation, perspective-taking and logic-puzzle tasks. Useful for planning, but not a direct test of long-running agents.
THE HEAD-TO-HEAD
Muse Spark 1.3
vs Gemini 3.8 Flash
Two models. The same task mix. Clear tradeoffs.
Thinking settings tested: xhigh / high.
Data reviewed · LiveBench question set: 25 June 2026 · View every source ↗ · Download the data ↓
Customize this comparison ↗Our take
Muse Spark 1.3 leads by 5.9 points on our General agent profile. Gemini 3.8 Flash has the lower baseline API estimate at $15 per 1,000 calls. Test both on your workflow before choosing.
Muse Spark 1.3Gemini 3.8 Flash
| Measure | Muse Spark 1.3xhigh | Gemini 3.8 Flashhigh |
|---|---|---|
| Agent Fit | 79.3 | 73.3 |
| Practical Value | 70.5 | 69.4 |
| Evidence Consensus | Insufficient evidence | 55.6 |
| Workload cost | $21 | $15 |
| Context window | 1.05M | 1.05M |
| Tool calling | Supported | Supported |
| Reasoning | 89.7 | 89.3 |
| Coding | 81.1 | 72.5 |
| Agentic coding | 64.1 | 54.2 |
| Mathematics | 96.0 | 91.6 |
| Data analysis | 79.6 | 54.0 |
| Language | 82.8 | 87.8 |
| Instruction following | 78.0 | 81.4 |
| Input / output per 1M | $1.25 / $4.25 | $0.75 / $3.75 |
Where their benchmark results differ
Coding
Muse Spark 1.3 leads by 8.6 points.
Can it write or complete code that passes tests? These are contained programming problems, not entire software projects.
Agentic coding
Muse Spark 1.3 leads by 9.8 points.
Can it edit code in a tool-using workflow? LiveBench tests JavaScript, TypeScript and Python tasks. Results depend on the testing software and tools as well as the model.
Mathematics
Muse Spark 1.3 leads by 4.4 points.
Can it solve difficult quantitative problems with checkable answers? Strong math is useful evidence of reasoning, but does not guarantee better writing or tool use.
Data analysis
Muse Spark 1.3 leads by 25.6 points.
Can it join and reformat tables and reason about event sequences? Useful for agents that process structured business information.
Language
Gemini 3.8 Flash leads by 5.0 points.
Can it interpret word relationships, reconstruct plots and correct typos? This is a narrow language test, not a full measure of writing quality or multilingual coverage.
Instruction following
Gemini 3.8 Flash leads by 3.4 points.
Can it follow requested constraints while rewriting, simplifying, summarizing and composing text? Relevant to agents that must return a specific format.
How to choose between them
Start with your task, not the overall winner. Coding agents need a strong edit-and-test loop; research agents need structured information handling; support agents need instructions followed consistently. Our default weights are only one interpretation of those needs.
Both models are compared on LiveBench’s 25 June 2026 question set. The tested reasoning configurations differ where shown. More thinking can improve results while changing token use and response time. No speed advantage is inferred from these scores.
Cost assumptions
All prices are USD. The baseline uses 1,000 calls with 10,000 input tokens and 2,000 billed output tokens per call. Include reasoning tokens; caching, tools, retries and provider premiums are excluded. Change the workload and weights to see whether the tradeoff changes.
Evidence and uncertainty
Consensus combines LiveBench and Arena only when the model version and thinking setting match. A missing score does not mean a model is worse. Small differences may change with the tasks, settings or repeated runs; the combined rating does not tell us how certain a difference is.
Compare quality and cost
Sweet-spot zoneStrong price–quality tradeoffsTap a dot to inspect
INSPECTINGGemini 3.8 Flash ↗
73.3Agent Fit$15your workloadYOUR FAST SHORTLIST
How we choose ↗Closest to the sweet spot
- 1Gemini 3.8 Flash ↗73.3 Agent Fit · $15
- 2Muse Spark 1.3 ↗79.3 Agent Fit · $21
Add more models for a meaningful zone. Numbers mark models with strong price–quality tradeoffs in or near this zone. On the dotted line, no other shown model is cheaper with an equal or higher score, or scores higher at the same price. Your chosen measure, usage and filters change this shortlist.