Model comparison
GPT-5.6 Sol vs Laguna S 2.1
Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Laguna S 2.1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Laguna S 2.1 share 4 comparable benchmark results. 2 of 8 categories are comparable. 42 results are unique to GPT-5.6 Sol; 2 to Laguna S 2.1.
Updated July 21, 2026- Shared results
- 4
- GPT-5.6 Sol only
- 42
- Laguna S 2.1 only
- 2
- Comparable categories
- 2 / 8
Treat this as a split decision. GPT-5.6 Sol makes more sense if agentic is the priority; Laguna S 2.1 is the better fit if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 2 evidence categories; 2 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 and Laguna S 2.1 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.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.10 input / $0.20 output per 1M tokens for Laguna S 2.1. That is roughly 150.0x on output cost alone.
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 | Laguna S 2.1 |
|---|---|---|---|
| Agentic | GPT-5.6 Sol92.0 | Margin← 21.8 | Laguna S 2.170.2 |
| Coding | GPT-5.6 Sol64.6 | Margin← 5.2 | Laguna S 2.159.4 |
| Knowledge | GPT-5.6 Sol94.6 | MarginNo overlap | Laguna S 2.1Not measured |
| Math | GPT-5.6 Sol87.5 | MarginNo overlap | Laguna S 2.1Not measured |
| Multimodal | GPT-5.6 Sol83.0 | MarginNo overlap | Laguna S 2.1Not 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 70.2%Winner: GPT-5.6 SolΔ 21.7Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Laguna S 2.1 scored 70.2%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.6%B 59.4%Winner: GPT-5.6 SolΔ 5.2SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Laguna S 2.1 scored 59.4%. 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 | Laguna S 2.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Laguna S 2.1$0.1 input / $0.2 output | Laguna S 2.1 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Laguna S 2.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Laguna S 2.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Laguna S 2.11M | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins18 benchmarks
| Benchmark | GPT-5.6 Sol | Laguna S 2.1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | 70.2% | GPT-5.6 Sol leads |
| BrowseCompSource | 92.2% | — | Not comparable |
| OSWorld 2.0Source | 62.6% | — | Not comparable |
| CyberGymSource | 84.5% | — | Not comparable |
| ExploitGymSource | 33.7% | — | Not comparable |
| ToolathlonSource | 58% | — | Not comparable |
| AA Agentic IndexSource | 54.0% | — | Not comparable |
| τ²-bench resultsSource | 85.1% | — | Not comparable |
| GDPval-AASource | 61.8% | — | Not comparable |
| GDPval-AASource | 1736 | — | Not comparable |
| AA BriefcaseSource | 1501 | — | Not comparable |
| AA ITBenchSource | 56.2% | — | Not comparable |
| AA Tau3 BankingSource | 33.0% | — | Not comparable |
| AA AutomationBenchSource | 51.2% | — | Not comparable |
| AA Harvey LABSource | 87.2% | — | Not comparable |
| terminalBenchHardSource | 65.9% | — | Not comparable |
| aaTerminalBench21Source | 88% | — | Not comparable |
| Toolathlon-VerifiedSource | — | 49.7% | Not comparable |
CodingGPT-5.6 Sol wins9 benchmarks
| Benchmark | GPT-5.6 Sol | Laguna S 2.1 | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | 59.4% | GPT-5.6 Sol leads |
| Terminal-Bench 2.0Source | 91.9% | 70.2% | GPT-5.6 Sol leads |
| deepSweSource | 72.7% | 40.4% | GPT-5.6 Sol leads |
| FrontierCode 1.1 ExtendedSource | 60.6% | — | Not comparable |
| cursorBench32Source | 67.2% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 77.4% | — | Not comparable |
| AA-SciCodeSource | 56.1% | — | Not comparable |
| SWE MultilingualSource | — | 78.5% | Not comparable |
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5.6 Sol | Laguna S 2.1 | Result |
|---|---|---|---|
| GPQASource | 94.6% | — | Not comparable |
| GPQA-DSource | 94.6% | — | Not comparable |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 58.9% | — | Not comparable |
| AA-GPQA DiamondSource | 94.1% | — | Not comparable |
| AA-HLESource | 47.2% | — | Not comparable |
| AA-Omniscience IndexSource | 21.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 58.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 88.8% | — | Not comparable |
Math3 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Sol | Laguna S 2.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.7% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, GPT-5.6 Sol or Laguna S 2.1?
GPT-5.6 Sol and Laguna S 2.1 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 coding, GPT-5.6 Sol or Laguna S 2.1?
GPT-5.6 Sol has the edge for coding in this comparison, averaging 64.6 versus 59.4. Inside this category, deepSwe is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.6 Sol or Laguna S 2.1?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 70.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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