Model comparison
GPT-5.2 vs Laguna S 2.1
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.2 #64 (Estimated); Laguna S 2.1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2 and Laguna S 2.1 share 1 comparable benchmark result. 2 of 8 categories are comparable. 27 results are unique to GPT-5.2; 5 to Laguna S 2.1.
Updated July 21, 2026- Shared results
- 1
- GPT-5.2 only
- 27
- Laguna S 2.1 only
- 5
- Comparable categories
- 2 / 8
Treat this as a split decision. GPT-5.2 makes more sense if coding is the priority; Laguna S 2.1 is the better fit if agentic is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 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-5.2 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-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.10 input / $0.20 output per 1M tokens for Laguna S 2.1. That is roughly 70.0x on output cost alone. Laguna S 2.1 gives you the larger context window at 1M, compared with 400K for GPT-5.2.
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-5.2 | Δ | Laguna S 2.1 |
|---|---|---|---|
| Agentic | GPT-5.255.7 | Margin→ 14.5 | Laguna S 2.170.2 |
| Coding | GPT-5.270.6 | Margin← 11.2 | Laguna S 2.159.4 |
| Reasoning | GPT-5.252.9 | MarginNo overlap | Laguna S 2.1Not measured |
| Knowledge | GPT-5.292.4 | MarginNo overlap | Laguna S 2.1Not measured |
| Math | GPT-5.235.2 | MarginNo overlap | Laguna S 2.1Not measured |
| Multimodal | GPT-5.280.4 | MarginNo overlap | Laguna S 2.1Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Pro
CodingA 55.6%B 59.4%Winner: Laguna S 2.1Δ 3.8SWE-bench Pro: GPT-5.2 scored 55.6%; Laguna S 2.1 scored 59.4%. Laguna S 2.1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.2 | Laguna S 2.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 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-5.273 tok/s | Laguna S 2.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | Laguna S 2.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2400K | Laguna S 2.11M | Laguna S 2.1 lists the larger context window. |
Benchmark Deep Dive
AgenticLaguna S 2.1 wins7 benchmarks
| Benchmark | GPT-5.2 | Laguna S 2.1 | Result |
|---|---|---|---|
| BrowseCompSource | 65.8% | — | Not comparable |
| OSWorld-VerifiedSource | 47.3% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | — | Not comparable |
| Gert LabsSource | 46.54% | — | Not comparable |
| JobBenchSource | 34.3% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 70.2% | Not comparable |
| Toolathlon-VerifiedSource | — | 49.7% | Not comparable |
CodingGPT-5.2 wins7 benchmarks
| Benchmark | GPT-5.2 | Laguna S 2.1 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80% | — | Not comparable |
| SWE-bench ProSource | 55.6% | 59.4% | Laguna S 2.1 leads |
| Vibe Code BenchSource | 53.50% | — | Not comparable |
| AA-SciCodeSource | 52.1% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 70.2% | Not comparable |
| SWE MultilingualSource | — | 78.5% | Not comparable |
| deepSweSource | — | 40.4% | Not comparable |
Reasoning3 benchmarks
Knowledge7 benchmarks
| Benchmark | GPT-5.2 | Laguna S 2.1 | Result |
|---|---|---|---|
| GPQASource | 92.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 42.2% | — | Not comparable |
| AA-GPQA DiamondSource | 90.3% | — | Not comparable |
| AA-HLESource | 35.4% | — | Not comparable |
| AA-Omniscience IndexSource | -1.0% | — | Not comparable |
| AA-Omniscience AccuracySource | 43.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 79.7% | — | Not comparable |
Math3 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.2 | Laguna S 2.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, GPT-5.2 or Laguna S 2.1?
GPT-5.2 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-5.2 or Laguna S 2.1?
GPT-5.2 has the edge for coding in this comparison, averaging 70.6 versus 59.4. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.2 or Laguna S 2.1?
Laguna S 2.1 has the edge for agentic tasks in this comparison, averaging 70.2 versus 55.7. GPT-5.2 stays close enough that the answer can still flip depending on your workload.
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