Model comparison
Muse Spark 1.1 vs SWE-1.7
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Muse Spark 1.1 #6 (Supported); SWE-1.7 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Muse Spark 1.1 and SWE-1.7 share 2 comparable benchmark results. 1 of 8 categories are comparable. 37 results are unique to Muse Spark 1.1; 2 to SWE-1.7.
Updated July 23, 2026- Shared results
- 2
- Muse Spark 1.1 only
- 37
- SWE-1.7 only
- 2
- Comparable categories
- 1 / 8
Treat this as a split decision. Muse Spark 1.1 makes more sense if you need the larger 1M context window; SWE-1.7 is the better fit if agentic is the priority.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Muse Spark 1.1 and SWE-1.7 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 1.1 gives you the larger context window at 1M, compared with 256K for SWE-1.7.
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 | Muse Spark 1.1 | Δ | SWE-1.7 |
|---|---|---|---|
| Agentic | Muse Spark 1.180.4 | Margin→ 1.1 | SWE-1.781.5 |
| Coding | Muse Spark 1.161.5 | MarginNo overlap | SWE-1.7Not measured |
| Knowledge | Muse Spark 1.162.1 | MarginNo overlap | SWE-1.7Not measured |
| Multimodal | Muse Spark 1.188.4 | MarginNo overlap | SWE-1.7Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 80%B 81.5%Winner: SWE-1.7Δ 1.5Terminal-Bench 2.0: Muse Spark 1.1 scored 80%; SWE-1.7 scored 81.5%. SWE-1.7 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Muse Spark 1.1 | SWE-1.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Muse Spark 1.1Not available | SWE-1.7Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Muse Spark 1.1Not available | SWE-1.7Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Muse Spark 1.1Not available | SWE-1.7Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Muse Spark 1.11M | SWE-1.7256K | Muse Spark 1.1 lists the larger context window. |
Benchmark Deep Dive
AgenticSWE-1.7 wins20 benchmarks
| Benchmark | Muse Spark 1.1 | SWE-1.7 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 80% | 81.5% | SWE-1.7 leads |
| MCP AtlasSource | 88.1% | — | Not comparable |
| ToolathlonSource | 75.6% | — | Not comparable |
| OSWorld-VerifiedSource | 80.8% | — | Not comparable |
| DeepSearchQASource | 84.9% | — | Not comparable |
| CyberGymSource | 59.0% | — | Not comparable |
| Finance Agent v2Source | 57.2% | — | Not comparable |
| deepSweSource | 53.3% | — | Not comparable |
| OSWorld 2.0Source | 14.2% | — | Not comparable |
| JobBenchSource | 54.7% | — | Not comparable |
| CybenchSource | 92.9% | — | Not comparable |
| ExploitGymSource | 0.8% | — | Not comparable |
| AA Agentic IndexSource | 37.5% | — | Not comparable |
| GDPval-AASource | 43.7% | — | Not comparable |
| GDPval-AASource | 1374 | — | Not comparable |
| AA BriefcaseSource | 863 | — | Not comparable |
| AA AutomationBenchSource | 42.8% | — | Not comparable |
| AA Harvey LABSource | 93.1% | — | Not comparable |
| AA Tau3 BankingSource | 25.2% | — | Not comparable |
| aaTerminalBench21Source | 77.9% | — | Not comparable |
Coding6 benchmarks
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | Muse Spark 1.1 | SWE-1.7 | Result |
|---|---|---|---|
| HLESource | 62.1% | — | Not comparable |
| HLE w/o toolsSource | 52.2% | — | Not comparable |
| HealthBench ProfessionalSource | 59.3% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 50.6% | — | Not comparable |
| AA-GPQA DiamondSource | 89.8% | — | Not comparable |
| AA-HLESource | 45.1% | — | Not comparable |
| AA-Omniscience IndexSource | 18.0% | — | Not comparable |
| AA-Omniscience AccuracySource | 40.6% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 38.1% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, Muse Spark 1.1 or SWE-1.7?
Muse Spark 1.1 and SWE-1.7 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 agentic tasks, Muse Spark 1.1 or SWE-1.7?
SWE-1.7 has the edge for agentic tasks in this comparison, averaging 81.5 versus 80.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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