Model comparison

GPT-5.2 vs Laguna M.1

Data verified July 27, 2026

Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

GPT-5.2

OpenAI

57.62/100

No comparison

Laguna M.1

Poolside

N/A

2 category wins0 category wins

Public leaderboard positions: GPT-5.2 #71 (Estimated); Laguna M.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 M.1 share 2 comparable benchmark results. 2 of 8 categories are comparable. 26 results are unique to GPT-5.2; 3 to Laguna M.1.

Updated July 27, 2026

Shared results: 2
GPT-5.2 only: 26
Laguna M.1 only: 3
Comparable categories: 2 / 8

Treat this as a split decision. GPT-5.2 makes more sense if agentic is the priority or you need the larger 400K context window; Laguna M.1 is the better fit if its strengths line up with your actual workload.

Confidence note. This is a partial-evidence comparison with 2 shared benchmark results 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 M.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 gives you the larger context window at 400K, compared with 256K for Laguna M.1.

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-5.2 and Laguna M.1
Category	GPT-5.2	Δ	Laguna M.1
Agentic	GPT-5.255.7	Margin← 9.9	Laguna M.145.8
Coding	GPT-5.270.6	Margin← 5.8	Laguna M.164.8
Reasoning	GPT-5.252.9	MarginNo overlap	Laguna M.1Not measured
Knowledge	GPT-5.292.4	MarginNo overlap	Laguna M.1Not measured
Math	GPT-5.235.2	MarginNo overlap	Laguna M.1Not measured
Multimodal	GPT-5.280.4	MarginNo overlap	Laguna M.1Not measured

Decisive benchmark drivers

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

A · GPT-5.2B · Laguna M.1

SWE-bench Pro
Coding
Source ↗
A 55.6%B 49.2%
Winner: GPT-5.2Δ 6.4
SWE-bench Pro: GPT-5.2 scored 55.6%; Laguna M.1 scored 49.2%. GPT-5.2 wins this benchmark.
SWE-bench Verified
Coding
Source ↗
A 80%B 74.6%
Winner: GPT-5.2Δ 5.4
SWE-bench Verified: GPT-5.2 scored 80%; Laguna M.1 scored 74.6%. GPT-5.2 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 M.1	Comparison
Input / output priceUSD per 1M tokens	GPT-5.2$1.75 input / $14 output	Laguna M.1Not available	A complete price comparison is not available.
Generation speedtokens per second	GPT-5.273 tok/s	Laguna M.1Not available	A complete speed comparison is not available.
First-answer latencyseconds to first token	GPT-5.2130.34 s	Laguna M.1Not available	A complete latency comparison is not available.
Context windowmaximum listed tokens	GPT-5.2400K	Laguna M.1256K	GPT-5.2 lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.2 wins

6 benchmarks

Benchmark	GPT-5.2	Laguna M.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	—	45.8%	Not comparable

CodingGPT-5.2 wins

6 benchmarks

Benchmark	GPT-5.2	Laguna M.1	Result
SWE-bench VerifiedSource	80%	74.6%	GPT-5.2 leads
SWE-bench ProSource	55.6%	49.2%	GPT-5.2 leads
Vibe Code BenchSource	53.50%	—	Not comparable
AA-SciCodeSource	52.1%	—	Not comparable
SWE MultilingualSource	—	63.1%	Not comparable
Terminal-Bench 2.0Source	—	45.8%	Not comparable

Reasoning

3 benchmarks

Benchmark	GPT-5.2	Laguna M.1	Result
ARC-AGI-2Source	52.9%	—	Not comparable
AA-LCRSource	72.7%	—	Not comparable
CritPtSource	11.6%	—	Not comparable

Knowledge

7 benchmarks

Benchmark	GPT-5.2	Laguna M.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

Math

3 benchmarks

Benchmark	GPT-5.2	Laguna M.1	Result
AA AIME 2025Source	99.0%	—	Not comparable
FrontierMath v2 (Tiers 1-3)Source	40.700%	—	Not comparable
FrontierMath v2 (Tier 4)Source	18.800%	—	Not comparable

Multimodal

5 benchmarks

Benchmark	GPT-5.2	Laguna M.1	Result
MMMU-ProSource	79.5%	—	Not comparable
MathVisionSource	83.0%	—	Not comparable
CharXivSource	82.1%	—	Not comparable
V*Source	75.9%	—	Not comparable
Design Arena WebsiteSource	1219	—	Not comparable

Inst. Following

1 benchmarks

Benchmark	GPT-5.2	Laguna M.1	Result
AA-IFBenchSource	75.4%	—	Not comparable

Frequently Asked Questions (3)

Which is better, GPT-5.2 or Laguna M.1?

GPT-5.2 and Laguna M.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 M.1?

GPT-5.2 has the edge for coding in this comparison, averaging 70.6 versus 64.8. 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 M.1?

GPT-5.2 has the edge for agentic tasks in this comparison, averaging 55.7 versus 45.8. Laguna M.1 stays close enough that the answer can still flip depending on your workload.

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Last updated: July 27, 2026

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