Model comparison
GPT-5.5 vs Muse Spark
Head-to-head evidence from 27 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.5 #9 (Estimated); Muse Spark #13 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.5 and Muse Spark share 27 comparable benchmark results. 6 of 8 categories are comparable. 30 results are unique to GPT-5.5; 12 to Muse Spark.
Updated July 23, 2026- Shared results
- 27
- GPT-5.5 only
- 30
- Muse Spark only
- 12
- Comparable categories
- 6 / 8
Pick GPT-5.5 if you want the stronger benchmark profile. Muse Spark only becomes the better choice if multimodal & grounded is the priority.
Confidence note. This is a partial-evidence comparison with 27 shared benchmark results across 7 evidence categories; 6 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.5 has the cleaner BenchAlign overall profile here, landing at 73.51 versus 71.04. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.5's sharpest advantage is in reasoning, where it averages 85 against 42.5. The single biggest benchmark swing on the page is ARC-AGI-2, 85% to 42.5%. Muse Spark does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
GPT-5.5 gives you the larger context window at 1M, compared with 262K for Muse Spark.
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 | GPT-5.5 | Δ | Muse Spark |
|---|---|---|---|
| Reasoning | GPT-5.585.0 | Margin← 42.5 | Muse Spark42.5 |
| Agentic | GPT-5.581.6 | Margin← 22.6 | Muse Spark59.0 |
| Math | GPT-5.547.6 | Margin← 14.7 | Muse Spark32.9 |
| Multimodal | GPT-5.570.4 | Margin→ 12.1 | Muse Spark82.5 |
| Coding | GPT-5.558.6 | Margin→ 9.2 | Muse Spark67.8 |
| Knowledge | GPT-5.557.8 | Margin← 7.4 | Muse Spark50.4 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
ARC-AGI-2
ReasoningA 85%B 42.5%Winner: GPT-5.5Δ 42.5ARC-AGI-2: GPT-5.5 scored 85%; Muse Spark scored 42.5%. GPT-5.5 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 82%B 59%Winner: GPT-5.5Δ 23Terminal-Bench 2.0: GPT-5.5 scored 82%; Muse Spark scored 59%. GPT-5.5 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 35.400%B 14.600%Winner: GPT-5.5Δ 20.8FrontierMath v2 (Tier 4): GPT-5.5 scored 35.400%; Muse Spark scored 14.600%. GPT-5.5 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 51.700%B 39.000%Winner: GPT-5.5Δ 12.7FrontierMath v2 (Tiers 1-3): GPT-5.5 scored 51.700%; Muse Spark scored 39.000%. GPT-5.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 58.6%B 52.4%Winner: GPT-5.5Δ 6.2SWE-bench Pro: GPT-5.5 scored 58.6%; Muse Spark scored 52.4%. GPT-5.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.5 | Muse Spark | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.5$5 input / $30 output | Muse SparkNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.5Not available | Muse SparkNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.5Not available | Muse SparkNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.51M | Muse Spark262K | GPT-5.5 lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.5 wins26 benchmarks
| Benchmark | GPT-5.5 | Muse Spark | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 82% | 59% | GPT-5.5 leads |
| CyberGymSource | 81.8% | 43.5% | GPT-5.5 leads |
| BrowseCompSource | 84.4% | — | Not comparable |
| OSWorld-VerifiedSource | 78.7% | — | Not comparable |
| MCP AtlasSource | 75.3% | — | Not comparable |
| ToolathlonSource | 55.6% | — | Not comparable |
| τ²-bench resultsSource | 93.9% | 91.5% | GPT-5.5 leads |
| AA Agentic IndexSource | 44.9% | 28.7% | GPT-5.5 leads |
| APEX-Agents-AASource | 37.7% | — | Not comparable |
| GDPval-AASource | 49.5% | 32.2% | GPT-5.5 leads |
| GDPval-AASource | 1490 | 1144 | GPT-5.5 leads |
| Gert LabsSource | 72.93% | — | Not comparable |
| ResearchClawBenchSource | 17.0% | — | Not comparable |
| OSWorld 2.0Source | 13.0% | — | Not comparable |
| JobBenchSource | 42.7% | — | Not comparable |
| ExploitGymSource | 13.4% | — | Not comparable |
| AA BriefcaseSource | 1154 | — | Not comparable |
| AA AutomationBenchSource | 42.1% | — | Not comparable |
| AA EnterpriseOps-GymSource | 46.6% | — | Not comparable |
| AA Harvey LABSource | 86.3% | — | Not comparable |
| AA ITBenchSource | 45.8% | — | Not comparable |
| AA Tau3 BankingSource | 31.3% | — | Not comparable |
| terminalBenchHardSource | 60.6% | — | Not comparable |
| aaTerminalBench21Source | 84.3% | — | Not comparable |
| DeepSearchQASource | — | 74.8% | Not comparable |
| Claw-EvalSource | — | 63.8% | Not comparable |
CodingMuse Spark wins11 benchmarks
| Benchmark | GPT-5.5 | Muse Spark | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.6% | 52.4% | GPT-5.5 leads |
| Terminal-Bench 2.0Source | 82.0% | — | Not comparable |
| Vibe Code BenchSource | 69.85% | 19.67% | GPT-5.5 leads |
| React Native EvalsSource | 84.7% | — | Not comparable |
| cursorBench31Source | 59.2% | — | Not comparable |
| cursorBench32Source | 58.4% | — | Not comparable |
| AA Coding IndexSource | 74.9% | 58.6% | GPT-5.5 leads |
| AA-SciCodeSource | 56.1% | 51.5% | GPT-5.5 leads |
| FrontierCode 1.1 MainSource | 43.0% | — | Not comparable |
| SWE-bench VerifiedSource | — | 77.4% | Not comparable |
| LiveCodeBench ProSource | — | 80.0% | Not comparable |
ReasoningGPT-5.5 wins5 benchmarks
KnowledgeGPT-5.5 wins12 benchmarks
| Benchmark | GPT-5.5 | Muse Spark | Result |
|---|---|---|---|
| GPQASource | 93.6% | — | Not comparable |
| GPQA-DSource | 93.6% | 89.5% | GPT-5.5 leads |
| HLESource | 52.2% | 50.4% | GPT-5.5 leads |
| HLE w/o toolsSource | 41.4% | 42.8% | Muse Spark leads |
| Artificial Analysis Intelligence IndexSource | 54.8% | 43.1% | GPT-5.5 leads |
| AA-GPQA DiamondSource | 93.5% | 88.4% | GPT-5.5 leads |
| AA-HLESource | 44.3% | 39.9% | GPT-5.5 leads |
| AA-Omniscience IndexSource | 20.1% | 4.1% | GPT-5.5 leads |
| AA-Omniscience AccuracySource | 56.9% | 44.6% | GPT-5.5 leads |
| AA-Omniscience Hallucination RateSource | 85.5% | 73.2% | Muse Spark leads |
| HealthBench HardSource | — | 42.8% | Not comparable |
| MedXpertQA (Text)Source | — | 52.6% | Not comparable |
MathGPT-5.5 wins3 benchmarks
MultimodalMuse Spark wins11 benchmarks
| Benchmark | GPT-5.5 | Muse Spark | Result |
|---|---|---|---|
| MMMU-ProSource | 81.2% | 80.4% | GPT-5.5 leads |
| MMMU-Pro w/ PythonSource | 83.2% | — | Not comparable |
| OfficeQA ProSource | 54.1% | — | Not comparable |
| AA-MMMU-ProSource | 79.9% | 80.5% | Muse Spark leads |
| Design Arena WebsiteSource | 1282 | — | Not comparable |
| CharXivSource | — | 86.4% | 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 |
Inst. Following1 benchmarks
| Benchmark | GPT-5.5 | Muse Spark | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | 75.9% | Tie |
Frequently Asked Questions (7)
Which is better, GPT-5.5 or Muse Spark?
GPT-5.5 is ahead on BenchLM's BenchAlign leaderboard, 73.51 to 71.04. The biggest single separator in this matchup is ARC-AGI-2, where the scores are 85% and 42.5%.
Which is better for knowledge tasks, GPT-5.5 or Muse Spark?
GPT-5.5 has the edge for knowledge tasks in this comparison, averaging 57.8 versus 50.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.5 or Muse Spark?
Muse Spark has the edge for coding in this comparison, averaging 67.8 versus 58.6. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.5 or Muse Spark?
GPT-5.5 has the edge for math in this comparison, averaging 47.6 versus 32.9. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.
Which is better for reasoning, GPT-5.5 or Muse Spark?
GPT-5.5 has the edge for reasoning in this comparison, averaging 85 versus 42.5. Inside this category, ARC-AGI-2 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.5 or Muse Spark?
GPT-5.5 has the edge for agentic tasks in this comparison, averaging 81.6 versus 59. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.5 or Muse Spark?
Muse Spark has the edge for multimodal and grounded tasks in this comparison, averaging 82.5 versus 70.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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