Model comparison
GPT-5.6 Sol vs Muse Spark 1.1
Head-to-head evidence from 26 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Muse Spark 1.1 #6 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Muse Spark 1.1 share 26 comparable benchmark results. 4 of 8 categories are comparable. 20 results are unique to GPT-5.6 Sol; 13 to Muse Spark 1.1.
Updated July 23, 2026- Shared results
- 26
- GPT-5.6 Sol only
- 20
- Muse Spark 1.1 only
- 13
- Comparable categories
- 4 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Muse Spark 1.1 only becomes the better choice if multimodal & grounded is the priority.
Confidence note. This is a partial-evidence comparison with 26 shared benchmark results across 4 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
GPT-5.6 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 77.44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol's sharpest advantage is in knowledge, where it averages 94.6 against 62.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 91.9% to 80%. Muse Spark 1.1 does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
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-5.6 Sol | Δ | Muse Spark 1.1 |
|---|---|---|---|
| Knowledge | GPT-5.6 Sol94.6 | Margin← 32.5 | Muse Spark 1.162.1 |
| Agentic | GPT-5.6 Sol92.0 | Margin← 11.6 | Muse Spark 1.180.4 |
| Multimodal | GPT-5.6 Sol83.0 | Margin→ 5.4 | Muse Spark 1.188.4 |
| Coding | GPT-5.6 Sol64.6 | Margin← 3.1 | Muse Spark 1.161.5 |
| Math | GPT-5.6 Sol87.5 | MarginNo overlap | Muse Spark 1.1Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 91.9%B 80%Winner: GPT-5.6 SolΔ 11.9Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Muse Spark 1.1 scored 80%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.6%B 61.5%Winner: GPT-5.6 SolΔ 3.1SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Muse Spark 1.1 scored 61.5%. GPT-5.6 Sol wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.6 Sol | Muse Spark 1.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Muse Spark 1.1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Muse Spark 1.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Muse Spark 1.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Muse Spark 1.11M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins24 benchmarks
| Benchmark | GPT-5.6 Sol | Muse Spark 1.1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | 80% | GPT-5.6 Sol leads |
| BrowseCompSource | 92.2% | — | Not comparable |
| OSWorld 2.0Source | 62.6% | 14.2% | GPT-5.6 Sol leads |
| CyberGymSource | 84.5% | 59.0% | GPT-5.6 Sol leads |
| ExploitGymSource | 33.7% | 0.8% | GPT-5.6 Sol leads |
| ToolathlonSource | 58% | 75.6% | Muse Spark 1.1 leads |
| AA Agentic IndexSource | 54.0% | 37.5% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 85.1% | — | Not comparable |
| GDPval-AASource | 61.8% | 43.7% | GPT-5.6 Sol leads |
| GDPval-AASource | 1736 | 1374 | GPT-5.6 Sol leads |
| AA BriefcaseSource | 1501 | 863 | GPT-5.6 Sol leads |
| AA ITBenchSource | 56.2% | — | Not comparable |
| AA Tau3 BankingSource | 33.0% | 25.2% | GPT-5.6 Sol leads |
| AA AutomationBenchSource | 51.2% | 42.8% | GPT-5.6 Sol leads |
| AA Harvey LABSource | 87.2% | 93.1% | Muse Spark 1.1 leads |
| terminalBenchHardSource | 65.9% | — | Not comparable |
| aaTerminalBench21Source | 88% | 77.9% | GPT-5.6 Sol leads |
| MCP AtlasSource | — | 88.1% | Not comparable |
| OSWorld-VerifiedSource | — | 80.8% | Not comparable |
| DeepSearchQASource | — | 84.9% | Not comparable |
| Finance Agent v2Source | — | 57.2% | Not comparable |
| deepSweSource | — | 53.3% | Not comparable |
| JobBenchSource | — | 54.7% | Not comparable |
| CybenchSource | — | 92.9% | Not comparable |
CodingGPT-5.6 Sol wins8 benchmarks
| Benchmark | GPT-5.6 Sol | Muse Spark 1.1 | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | 61.5% | GPT-5.6 Sol leads |
| Terminal-Bench 2.0Source | 91.9% | 80.0% | GPT-5.6 Sol leads |
| deepSweSource | 72.7% | — | Not comparable |
| FrontierCode 1.1 ExtendedSource | 60.6% | — | Not comparable |
| cursorBench32Source | 67.2% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 77.4% | 71.3% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 56.1% | 58.2% | Muse Spark 1.1 leads |
Reasoning5 benchmarks
KnowledgeGPT-5.6 Sol wins12 benchmarks
| Benchmark | GPT-5.6 Sol | Muse Spark 1.1 | Result |
|---|---|---|---|
| GPQASource | 94.6% | — | Not comparable |
| GPQA-DSource | 94.6% | — | Not comparable |
| HealthBench ProfessionalSource | 60.5% | 59.3% | GPT-5.6 Sol leads |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | 50.6% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 94.1% | 89.8% | GPT-5.6 Sol leads |
| AA-HLESource | 47.2% | 45.1% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | 21.7% | 18.0% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 58.5% | 40.6% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 88.8% | 38.1% | Muse Spark 1.1 leads |
| HLESource | — | 62.1% | Not comparable |
| HLE w/o toolsSource | — | 52.2% | Not comparable |
Math3 benchmarks
MultimodalMuse Spark 1.1 wins6 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Sol | Muse Spark 1.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.7% | — | Not comparable |
Frequently Asked Questions (5)
Which is better, GPT-5.6 Sol or Muse Spark 1.1?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 77.44. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 91.9% and 80%.
Which is better for knowledge tasks, GPT-5.6 Sol or Muse Spark 1.1?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 62.1. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.6 Sol or Muse Spark 1.1?
GPT-5.6 Sol has the edge for coding in this comparison, averaging 64.6 versus 61.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.6 Sol or Muse Spark 1.1?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 80.4. Inside this category, AA Briefcase is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.6 Sol or Muse Spark 1.1?
Muse Spark 1.1 has the edge for multimodal and grounded tasks in this comparison, averaging 88.4 versus 83. GPT-5.6 Sol stays close enough that the answer can still flip depending on your workload.
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