Model comparison
MAI-Thinking-1 vs Muse Spark
Head-to-head evidence from 4 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MAI-Thinking-1 unranked (Not scored); Muse Spark #13 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MAI-Thinking-1 and Muse Spark share 4 comparable benchmark results. 4 of 8 categories are comparable. 9 results are unique to MAI-Thinking-1; 35 to Muse Spark.
Updated July 23, 2026- Shared results
- 4
- MAI-Thinking-1 only
- 9
- Muse Spark only
- 35
- Comparable categories
- 4 / 8
Treat this as a split decision. MAI-Thinking-1 makes more sense if mathematics is the priority; Muse Spark is the better fit if agentic is the priority or you need the larger 262K context window.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 3 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MAI-Thinking-1 and Muse Spark finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Muse Spark gives you the larger context window at 262K, compared with 256K for MAI-Thinking-1.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | MAI-Thinking-1 | Δ | Muse Spark |
|---|---|---|---|
| Math | MAI-Thinking-189.7 | Margin← 56.8 | Muse Spark32.9 |
| Knowledge | MAI-Thinking-172.5 | Margin← 22.1 | Muse Spark50.4 |
| Agentic | MAI-Thinking-146.0 | Margin→ 13.0 | Muse Spark59.0 |
| Coding | MAI-Thinking-165.5 | Margin→ 2.3 | Muse Spark67.8 |
| Reasoning | MAI-Thinking-1Not measured | MarginNo overlap | Muse Spark42.5 |
| Multimodal | MAI-Thinking-1Not measured | MarginNo overlap | Muse Spark82.5 |
| Inst. Following | MAI-Thinking-185.0 | MarginNo overlap | Muse SparkNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 46%B 59%Winner: Muse SparkΔ 13Terminal-Bench 2.0: MAI-Thinking-1 scored 46%; Muse Spark scored 59%. Muse Spark wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 73.5%B 77.4%Winner: Muse SparkΔ 3.9SWE-bench Verified: MAI-Thinking-1 scored 73.5%; Muse Spark scored 77.4%. Muse Spark wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 52.8%B 52.4%Winner: MAI-Thinking-1Δ 0.4SWE-bench Pro: MAI-Thinking-1 scored 52.8%; Muse Spark scored 52.4%. MAI-Thinking-1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MAI-Thinking-1 | Muse Spark | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MAI-Thinking-1Not available | Muse SparkNot available | A complete price comparison is not available. |
| Generation speedtokens per second | MAI-Thinking-1Not available | Muse SparkNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MAI-Thinking-1Not available | Muse SparkNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MAI-Thinking-1256K | Muse Spark262K | Muse Spark lists the larger context window. |
Benchmark Deep Dive
AgenticMuse Spark wins8 benchmarks
| Benchmark | MAI-Thinking-1 | Muse Spark | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 46% | 59% | Muse Spark leads |
| τ²-bench resultsSource | — | 91.5% | Not comparable |
| DeepSearchQASource | — | 74.8% | Not comparable |
| CyberGymSource | — | 43.5% | Not comparable |
| Claw-EvalSource | — | 63.8% | Not comparable |
| AA Agentic IndexSource | — | 28.7% | Not comparable |
| GDPval-AASource | — | 32.2% | Not comparable |
| GDPval-AASource | — | 1144 | Not comparable |
CodingMuse Spark wins7 benchmarks
| Benchmark | MAI-Thinking-1 | Muse Spark | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.5% | 77.4% | Muse Spark leads |
| SWE-bench ProSource | 52.8% | 52.4% | MAI-Thinking-1 leads |
| Terminal-Bench 2.0Source | 46.0% | — | Not comparable |
| LiveCodeBench ProSource | — | 80.0% | Not comparable |
| Vibe Code BenchSource | — | 19.67% | Not comparable |
| AA Coding IndexSource | — | 58.6% | Not comparable |
| AA-SciCodeSource | — | 51.5% | Not comparable |
Reasoning4 benchmarks
KnowledgeMAI-Thinking-1 wins14 benchmarks
| Benchmark | MAI-Thinking-1 | Muse Spark | Result |
|---|---|---|---|
| GPQASource | 84.2% | — | Not comparable |
| GPQA-DSource | 84.2% | 89.5% | Muse Spark leads |
| MMLU-ProSource | 85% | — | Not comparable |
| SimpleQASource | 31% | — | Not comparable |
| HLESource | — | 50.4% | Not comparable |
| HLE w/o toolsSource | — | 42.8% | Not comparable |
| HealthBench HardSource | — | 42.8% | Not comparable |
| MedXpertQA (Text)Source | — | 52.6% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 43.1% | Not comparable |
| AA-GPQA DiamondSource | — | 88.4% | Not comparable |
| AA-HLESource | — | 39.9% | Not comparable |
| AA-Omniscience IndexSource | — | 4.1% | Not comparable |
| AA-Omniscience AccuracySource | — | 44.6% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 73.2% | Not comparable |
MathMAI-Thinking-1 wins5 benchmarks
Multimodal8 benchmarks
| Benchmark | MAI-Thinking-1 | Muse Spark | Result |
|---|---|---|---|
| CharXivSource | — | 86.4% | Not comparable |
| MMMU-ProSource | — | 80.4% | Not comparable |
| ERQASource | — | 64.7% | Not comparable |
| SimpleVQASource | — | 71.3% | Not comparable |
| ScreenSpot ProSource | — | 84.1% | Not comparable |
| ZeroBenchSource | — | 33.0% | Not comparable |
| MedXpertQA (MM)Source | — | 78.4% | Not comparable |
| AA-MMMU-ProSource | — | 80.5% | Not comparable |
Frequently Asked Questions (5)
Which is better, MAI-Thinking-1 or Muse Spark?
MAI-Thinking-1 and Muse Spark are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, MAI-Thinking-1 or Muse Spark?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 50.4. Inside this category, GPQA-D is the benchmark that creates the most daylight between them.
Which is better for coding, MAI-Thinking-1 or Muse Spark?
Muse Spark has the edge for coding in this comparison, averaging 67.8 versus 65.5. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, MAI-Thinking-1 or Muse Spark?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 32.9. Muse Spark stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, MAI-Thinking-1 or Muse Spark?
Muse Spark has the edge for agentic tasks in this comparison, averaging 59 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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