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Model comparison

Claude Opus 4.5 vs Laguna S 2.1

Data verified

Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.22/100
No comparison
Laguna S 2.1
Poolside
N/A
1 category wins1 category wins

Public leaderboard positions: Claude Opus 4.5 #34 (Supported); Laguna S 2.1 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 S 2.1 share 3 comparable benchmark results. 2 of 8 categories are comparable. 56 results are unique to Claude Opus 4.5; 3 to Laguna S 2.1.

Updated July 21, 2026
Shared results
3
Claude Opus 4.5 only
56
Laguna S 2.1 only
3
Comparable categories
2 / 8

Treat this as a split decision. Claude Opus 4.5 makes more sense if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model; 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 3 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 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.

Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.10 input / $0.20 output per 1M tokens for Laguna S 2.1. That is roughly 125.0x on output cost alone. Laguna S 2.1 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 S 2.1 gives you the larger context window at 1M, 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 scores and score margins for Claude Opus 4.5 and Laguna S 2.1
CategoryClaude Opus 4.5ΔLaguna S 2.1
CodingClaude Opus 4.571.7Margin← 12.3Laguna S 2.159.4
AgenticClaude Opus 4.562.6Margin→ 7.6Laguna S 2.170.2
ReasoningClaude Opus 4.564.4MarginNo overlapLaguna S 2.1Not measured
KnowledgeClaude Opus 4.558.1MarginNo overlapLaguna S 2.1Not measured
MathClaude Opus 4.557.5MarginNo overlapLaguna S 2.1Not measured
MultilingualClaude Opus 4.585.7MarginNo overlapLaguna S 2.1Not measured
MultimodalClaude Opus 4.569.9MarginNo overlapLaguna S 2.1Not measured
Inst. FollowingClaude Opus 4.569.5MarginNo overlapLaguna S 2.1Not measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Claude Opus 4.5B · Laguna S 2.1

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 59.3%B 70.2%
    Winner: Laguna S 2.1Δ 10.9
    Terminal-Bench 2.0: Claude Opus 4.5 scored 59.3%; Laguna S 2.1 scored 70.2%. Laguna S 2.1 wins this benchmark.

  2. SWE-bench Pro

    Coding
    Source ↗
    A 57.1%B 59.4%
    Winner: Laguna S 2.1Δ 2.3
    SWE-bench Pro: Claude Opus 4.5 scored 57.1%; 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.

MetricClaude Opus 4.5Laguna S 2.1Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.5$5 input / $25 outputLaguna S 2.1$0.1 input / $0.2 outputLaguna S 2.1 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.546 tok/sLaguna S 2.1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.51.01 sLaguna S 2.1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.5200KLaguna S 2.11MLaguna S 2.1 lists the larger context window.

Benchmark Deep Dive

AgenticLaguna S 2.1 wins
BenchmarkClaude Opus 4.5Laguna S 2.1Result
Terminal-Bench 2.0Source 59.3%70.2%Laguna S 2.1 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
Toolathlon-VerifiedSource —49.7%Not comparable
CodingClaude Opus 4.5 wins
BenchmarkClaude Opus 4.5Laguna S 2.1Result
SWE-bench VerifiedSource 80.9%—Not comparable
LiveCodeBench v6Source 84.8%—Not comparable
SWE-bench ProSource 57.1%59.4%Laguna S 2.1 leads
SWE MultilingualSource 77.5%78.5%Laguna S 2.1 leads
NL2RepoSource 43.2%—Not comparable
AA-SciCodeSource 47.0%—Not comparable
Terminal-Bench 2.0Source —70.2%Not comparable
deepSweSource —40.4%Not comparable
Reasoning
BenchmarkClaude Opus 4.5Laguna S 2.1Result
LongBench v2Source 64.4%—Not comparable
AI-NeedleSource 74%—Not comparable
AA-LCRSource 65.3%—Not comparable
CritPtSource 0.3%—Not comparable
Knowledge
BenchmarkClaude Opus 4.5Laguna S 2.1Result
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
Math
BenchmarkClaude Opus 4.5Laguna S 2.1Result
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
Multilingual
BenchmarkClaude Opus 4.5Laguna S 2.1Result
MMLU-ProXSource 85.7%—Not comparable
NOVA-63Source 56.7%—Not comparable
Multimodal
BenchmarkClaude Opus 4.5Laguna S 2.1Result
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 1277—Not comparable
Inst. Following
BenchmarkClaude Opus 4.5Laguna S 2.1Result
IFEvalSource 90.9%—Not comparable
IFBenchSource 58%—Not comparable
AA-IFBenchSource 43.0%—Not comparable
Frequently Asked Questions (3)

Which is better, Claude Opus 4.5 or Laguna S 2.1?

Claude Opus 4.5 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, Claude Opus 4.5 or Laguna S 2.1?

Claude Opus 4.5 has the edge for coding in this comparison, averaging 71.7 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, Claude Opus 4.5 or Laguna S 2.1?

Laguna S 2.1 has the edge for agentic tasks in this comparison, averaging 70.2 versus 62.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

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