Model comparison
Claude Opus 4.5 vs Laguna XS.2
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: Claude Opus 4.5 #39 (Supported); Laguna XS.2 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.5 and Laguna XS.2 share 4 comparable benchmark results. 2 of 8 categories are comparable. 55 results are unique to Claude Opus 4.5; 1 to Laguna XS.2.
Updated July 27, 2026- Shared results
- 4
- Claude Opus 4.5 only
- 55
- Laguna XS.2 only
- 1
- Comparable categories
- 2 / 8
Treat this as a split decision. Claude Opus 4.5 makes more sense if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model; Laguna XS.2 is the better fit if you want the cheaper token bill or you need the larger 256K context window.
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
Claude Opus 4.5 and Laguna XS.2 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.
Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna XS.2. That is roughly Infinityx on output cost alone. Laguna XS.2 is the reasoning model in the pair, while Claude Opus 4.5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Laguna XS.2 gives you the larger context window at 256K, compared with 200K for Claude Opus 4.5.
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 | Claude Opus 4.5 | Δ | Laguna XS.2 |
|---|---|---|---|
| Agentic | Claude Opus 4.562.6 | Margin← 26.9 | Laguna XS.235.7 |
| Coding | Claude Opus 4.571.7 | Margin← 10.9 | Laguna XS.260.8 |
| Reasoning | Claude Opus 4.564.4 | MarginNo overlap | Laguna XS.2Not measured |
| Knowledge | Claude Opus 4.558.1 | MarginNo overlap | Laguna XS.2Not measured |
| Math | Claude Opus 4.557.5 | MarginNo overlap | Laguna XS.2Not measured |
| Multilingual | Claude Opus 4.585.7 | MarginNo overlap | Laguna XS.2Not measured |
| Multimodal | Claude Opus 4.569.9 | MarginNo overlap | Laguna XS.2Not measured |
| Inst. Following | Claude Opus 4.569.5 | MarginNo overlap | Laguna XS.2Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 59.3%B 35.7%Winner: Claude Opus 4.5Δ 23.6Terminal-Bench 2.0: Claude Opus 4.5 scored 59.3%; Laguna XS.2 scored 35.7%. Claude Opus 4.5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 80.9%B 69.9%Winner: Claude Opus 4.5Δ 11SWE-bench Verified: Claude Opus 4.5 scored 80.9%; Laguna XS.2 scored 69.9%. Claude Opus 4.5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 57.1%B 46.3%Winner: Claude Opus 4.5Δ 10.8SWE-bench Pro: Claude Opus 4.5 scored 57.1%; Laguna XS.2 scored 46.3%. Claude Opus 4.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.5 | Laguna XS.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.5$5 input / $25 output | Laguna XS.2$0 input / $0 output | Laguna XS.2 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.546 tok/s | Laguna XS.2Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.51.01 s | Laguna XS.2Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.5200K | Laguna XS.2256K | Laguna XS.2 lists the larger context window. |
Benchmark Deep Dive
AgenticClaude Opus 4.5 wins16 benchmarks
| Benchmark | Claude Opus 4.5 | Laguna XS.2 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.3% | 35.7% | Claude Opus 4.5 leads |
| OSWorld-VerifiedSource | 66.3% | — | Not comparable |
| OSWorldSource | 66.3% | — | Not comparable |
| Claw-EvalSource | 59.6% | — | Not comparable |
| QwenClawBenchSource | 52.3% | — | Not comparable |
| τ³-bench resultsSource | 70.2% | — | Not comparable |
| VITA-BenchSource | 23.3% | — | Not comparable |
| DeepPlanningSource | 26.4% | — | Not comparable |
| ToolathlonSource | 43.5% | — | Not comparable |
| MCP AtlasSource | 42.3% | — | Not comparable |
| MCP-TasksSource | 71.8% | — | Not comparable |
| WideResearchSource | 76.4% | — | Not comparable |
| CyberGymSource | 50.6% | — | Not comparable |
| τ²-bench resultsSource | 86.3% | — | Not comparable |
| Gert LabsSource | 64.23% | — | Not comparable |
| JobBenchSource | 32.3% | — | Not comparable |
CodingClaude Opus 4.5 wins7 benchmarks
| Benchmark | Claude Opus 4.5 | Laguna XS.2 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80.9% | 69.9% | Claude Opus 4.5 leads |
| LiveCodeBench v6Source | 84.8% | — | Not comparable |
| SWE-bench ProSource | 57.1% | 46.3% | Claude Opus 4.5 leads |
| SWE MultilingualSource | 77.5% | 57.7% | Claude Opus 4.5 leads |
| NL2RepoSource | 43.2% | — | Not comparable |
| AA-SciCodeSource | 47.0% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 35.7% | Not comparable |
Reasoning4 benchmarks
Knowledge13 benchmarks
| Benchmark | Claude Opus 4.5 | Laguna XS.2 | Result |
|---|---|---|---|
| GPQASource | 87% | — | Not comparable |
| SuperGPQASource | 70.6% | — | Not comparable |
| MMLU-ProSource | 89.5% | — | Not comparable |
| MMLU-ReduxSource | 96.6% | — | Not comparable |
| C-EvalSource | 92.2% | — | Not comparable |
| HLESource | 30.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 34.7% | — | Not comparable |
| AA-GPQA DiamondSource | 81.0% | — | Not comparable |
| AA-HLESource | 12.9% | — | Not comparable |
| AA-Omniscience IndexSource | -3.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 40.7% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 75.4% | — | Not comparable |
| AA MMLU-ProSource | 88.9% | — | Not comparable |
Math7 benchmarks
| Benchmark | Claude Opus 4.5 | Laguna XS.2 | Result |
|---|---|---|---|
| AIME26Source | 95.1% | — | Not comparable |
| HMMT Feb 2025Source | 92.9% | — | Not comparable |
| HMMT Nov 2025Source | 93.3% | — | Not comparable |
| HMMT Feb 2026Source | 85.3% | — | Not comparable |
| MMAnswerBenchSource | 84.0% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 20.690% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 4.167% | — | Not comparable |
Multilingual2 benchmarks
Multimodal8 benchmarks
| Benchmark | Claude Opus 4.5 | Laguna XS.2 | Result |
|---|---|---|---|
| MMMU-ProSource | 70.6% | — | Not comparable |
| MathVisionSource | 74.3% | — | Not comparable |
| CharXivSource | 68.5% | — | Not comparable |
| VideoMMMUSource | 84.4% | — | Not comparable |
| ScreenSpot ProSource | 45.7% | — | Not comparable |
| V*Source | 67.0% | — | Not comparable |
| AA-MMMU-ProSource | 71.2% | — | Not comparable |
| Design Arena WebsiteSource | 1272 | — | Not comparable |
Frequently Asked Questions (3)
Which is better, Claude Opus 4.5 or Laguna XS.2?
Claude Opus 4.5 and Laguna XS.2 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, Claude Opus 4.5 or Laguna XS.2?
Claude Opus 4.5 has the edge for coding in this comparison, averaging 71.7 versus 60.8. Inside this category, SWE Multilingual is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Claude Opus 4.5 or Laguna XS.2?
Claude Opus 4.5 has the edge for agentic tasks in this comparison, averaging 62.6 versus 35.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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