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Model comparison

GPT-5.3 Codex vs Laguna S 2.1

Data verified

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

66.69/100
No comparison
Laguna S 2.1
Poolside
N/A
2 category wins0 category wins

Public leaderboard positions: GPT-5.3 Codex #26 (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-5.3 Codex and Laguna S 2.1 share 2 comparable benchmark results. 2 of 8 categories are comparable. 19 results are unique to GPT-5.3 Codex; 4 to Laguna S 2.1.

Updated July 21, 2026
Shared results
2
GPT-5.3 Codex only
19
Laguna S 2.1 only
4
Comparable categories
2 / 8

Treat this as a split decision. GPT-5.3 Codex makes more sense if coding is the priority; Laguna S 2.1 is the better fit if you want the cheaper token bill or you need the larger 1M context window.

Confidence note. This is a partial-evidence comparison with 2 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-5.3 Codex 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-5.3 Codex 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-5.3 Codex.

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 GPT-5.3 Codex and Laguna S 2.1
CategoryGPT-5.3 CodexΔLaguna S 2.1
CodingGPT-5.3 Codex67.2Margin← 7.8Laguna S 2.159.4
AgenticGPT-5.3 Codex71.4Margin← 1.2Laguna S 2.170.2

Decisive benchmark drivers

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

More
A · GPT-5.3 CodexB · Laguna S 2.1

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 77.3%B 70.2%
    Winner: GPT-5.3 CodexΔ 7.1
    Terminal-Bench 2.0: GPT-5.3 Codex scored 77.3%; Laguna S 2.1 scored 70.2%. GPT-5.3 Codex wins this benchmark.

  2. SWE-bench Pro

    Coding
    Source ↗
    A 56.8%B 59.4%
    Winner: Laguna S 2.1Δ 2.6
    SWE-bench Pro: GPT-5.3 Codex scored 56.8%; 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.

MetricGPT-5.3 CodexLaguna S 2.1Comparison
Input / output priceUSD per 1M tokensGPT-5.3 Codex$1.75 input / $14 outputLaguna S 2.1$0.1 input / $0.2 outputLaguna S 2.1 has the lower combined listed price.
Generation speedtokens per secondGPT-5.3 Codex79 tok/sLaguna S 2.1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-5.3 Codex88.26 sLaguna S 2.1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-5.3 Codex400KLaguna S 2.11MLaguna S 2.1 lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.3 Codex wins
BenchmarkGPT-5.3 CodexLaguna S 2.1Result
Terminal-Bench 2.0Source 77.3%70.2%GPT-5.3 Codex leads
OSWorld-VerifiedSource 64.7%—Not comparable
τ²-bench resultsSource 86%—Not comparable
Gert LabsSource 57.47%—Not comparable
JobBenchSource 33.7%—Not comparable
Toolathlon-VerifiedSource —49.7%Not comparable
CodingGPT-5.3 Codex wins
BenchmarkGPT-5.3 CodexLaguna S 2.1Result
SWE-bench VerifiedSource 85%—Not comparable
SWE-bench ProSource 56.8%59.4%Laguna S 2.1 leads
SWE-RebenchSource 58.2%—Not comparable
Vibe Code BenchSource 61.77%—Not comparable
AA-SciCodeSource 53.2%—Not comparable
Terminal-Bench 2.0Source —70.2%Not comparable
SWE MultilingualSource —78.5%Not comparable
deepSweSource —40.4%Not comparable
Reasoning
BenchmarkGPT-5.3 CodexLaguna S 2.1Result
AA-LCRSource 74.0%—Not comparable
CritPtSource 16.9%—Not comparable
Knowledge
BenchmarkGPT-5.3 CodexLaguna S 2.1Result
Artificial Analysis Intelligence IndexSource 44.3%—Not comparable
AA-GPQA DiamondSource 91.5%—Not comparable
AA-HLESource 39.9%—Not comparable
AA-Omniscience IndexSource 9.9%—Not comparable
AA-Omniscience AccuracySource 51.8%—Not comparable
AA-Omniscience Hallucination RateSource 86.9%—Not comparable
Multimodal
BenchmarkGPT-5.3 CodexLaguna S 2.1Result
AA-MMMU-ProSource 78.5%—Not comparable
Design Arena WebsiteSource 1193—Not comparable
Inst. Following
BenchmarkGPT-5.3 CodexLaguna S 2.1Result
AA-IFBenchSource 75.4%—Not comparable
Frequently Asked Questions (3)

Which is better, GPT-5.3 Codex or Laguna S 2.1?

GPT-5.3 Codex 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-5.3 Codex or Laguna S 2.1?

GPT-5.3 Codex has the edge for coding in this comparison, averaging 67.2 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-5.3 Codex or Laguna S 2.1?

GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.4 versus 70.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

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Last updated: July 21, 2026

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