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Model comparison

GPT-5.2-Codex vs Trinity-Large-Preview

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

59.1/100
Margin
3.2pts
← winning
55.94/100
0 category wins0 category wins

Public leaderboard positions: GPT-5.2-Codex #58 (Supported); Trinity-Large-Preview #79 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.2-Codex and Trinity-Large-Preview share 11 comparable benchmark results. 0 of 8 categories are comparable. 4 results are unique to GPT-5.2-Codex; 7 to Trinity-Large-Preview.

Updated July 21, 2026
Shared results
11
GPT-5.2-Codex only
4
Trinity-Large-Preview only
7
Comparable categories
0 / 8

Benchmark data for GPT-5.2-Codex and Trinity-Large-Preview is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

GPT-5.2-Codex is priced at $1.75 input / $14.00 output per 1M tokens, versus $0.25 input / $1.00 output per 1M tokens for Trinity-Large-Preview. Trinity-Large-Preview has the larger context window at 512K, compared with 400K for GPT-5.2-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.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGPT-5.2-CodexTrinity-Large-PreviewComparison
Input / output priceUSD per 1M tokensGPT-5.2-Codex$1.75 input / $14 outputTrinity-Large-Preview$0.25 input / $1 outputTrinity-Large-Preview has the lower combined listed price.
Generation speedtokens per secondGPT-5.2-Codex123 tok/sTrinity-Large-PreviewNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-5.2-Codex87.34 sTrinity-Large-PreviewNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-5.2-Codex400KTrinity-Large-Preview512KTrinity-Large-Preview lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGPT-5.2-CodexTrinity-Large-PreviewResult
τ²-bench resultsSource 92.1%90.1%GPT-5.2-Codex leads
Gert LabsSource 51.79%Not comparable
JobBenchSource 26.0%Not comparable
GDPval-AASource 2.7%Not comparable
GDPval-AASource 554Not comparable
Coding
BenchmarkGPT-5.2-CodexTrinity-Large-PreviewResult
Vibe Code BenchSource 37.91%Not comparable
AA-SciCodeSource 54.6%36.1%GPT-5.2-Codex leads
Reasoning
BenchmarkGPT-5.2-CodexTrinity-Large-PreviewResult
AA-LCRSource 75.7%33.0%GPT-5.2-Codex leads
CritPtSource 8.7%0.9%GPT-5.2-Codex leads
Knowledge
BenchmarkGPT-5.2-CodexTrinity-Large-PreviewResult
Artificial Analysis Intelligence IndexSource 40.1%24.5%GPT-5.2-Codex leads
AA-GPQA DiamondSource 89.9%75.2%GPT-5.2-Codex leads
AA-HLESource 33.5%14.7%GPT-5.2-Codex leads
AA-Omniscience IndexSource -2.5%-44.2%GPT-5.2-Codex leads
AA-Omniscience AccuracySource 40.7%22.8%GPT-5.2-Codex leads
AA-Omniscience Hallucination RateSource 72.8%86.6%GPT-5.2-Codex leads
MMLUSource 87.2%Not comparable
MMLU-Pro (Arcee)Source 75.2%Not comparable
GPQA-DSource 63.3%Not comparable
Math
BenchmarkGPT-5.2-CodexTrinity-Large-PreviewResult
AIME25 (Arcee)Source 24.0%Not comparable
Multimodal
BenchmarkGPT-5.2-CodexTrinity-Large-PreviewResult
AA-MMMU-ProSource 76.3%Not comparable
Design Arena WebsiteSource 1165Not comparable
Inst. Following
BenchmarkGPT-5.2-CodexTrinity-Large-PreviewResult
AA-IFBenchSource 77.6%56.3%GPT-5.2-Codex leads
Frequently Asked Questions (3)

Can I compare GPT-5.2-Codex and Trinity-Large-Preview on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for GPT-5.2-Codex and Trinity-Large-Preview today?

GPT-5.2-Codex: $1.75 input / $14.00 output per 1M tokens Trinity-Large-Preview: $0.25 input / $1.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

Related Comparisons

Last updated: July 21, 2026

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