Skip to main content

Model comparison

GLM-5.1 vs Trinity-Large-Preview

Data verified

Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

67.74/100
Margin
11.8pts
← winning
55.94/100
0 category wins0 category wins

Public leaderboard positions: GLM-5.1 #18 (Supported); Trinity-Large-Preview #79 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-5.1 and Trinity-Large-Preview share 15 comparable benchmark results. 0 of 8 categories are comparable. 21 results are unique to GLM-5.1; 3 to Trinity-Large-Preview.

Updated July 21, 2026
Shared results
15
GLM-5.1 only
21
Trinity-Large-Preview only
3
Comparable categories
0 / 8

Benchmark data for GLM-5.1 and Trinity-Large-Preview is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 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.

GLM-5.1 is priced at $1.40 input / $4.40 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 203K for GLM-5.1.

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 GLM-5.1 and Trinity-Large-Preview
CategoryGLM-5.1ΔTrinity-Large-Preview
AgenticGLM-5.165.4MarginNo overlapTrinity-Large-PreviewNot measured
CodingGLM-5.161.3MarginNo overlapTrinity-Large-PreviewNot measured
KnowledgeGLM-5.152.3MarginNo overlapTrinity-Large-PreviewNot measured
MathGLM-5.162.0MarginNo overlapTrinity-Large-PreviewNot measured

Operational comparison

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

MetricGLM-5.1Trinity-Large-PreviewComparison
Input / output priceUSD per 1M tokensGLM-5.1$1.4 input / $4.4 outputTrinity-Large-Preview$0.25 input / $1 outputTrinity-Large-Preview has the lower combined listed price.
Generation speedtokens per secondGLM-5.1Not availableTrinity-Large-PreviewNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-5.1Not availableTrinity-Large-PreviewNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-5.1203KTrinity-Large-Preview512KTrinity-Large-Preview lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-5.1Trinity-Large-PreviewResult
Terminal-Bench 2.0Source 63.5%Not comparable
BrowseCompSource 68%Not comparable
τ³-bench resultsSource 70.6%Not comparable
MCP AtlasSource 71.8%Not comparable
CyberGymSource 68.7%Not comparable
Claw-EvalSource 62.3%Not comparable
AA Agentic IndexSource 29.9%Not comparable
τ²-bench resultsSource 97.7%90.1%GLM-5.1 leads
GDPval-AASource 37.8%2.7%GLM-5.1 leads
Gert LabsSource 60.11%Not comparable
GDPval-AASource 1257554GLM-5.1 leads
ResearchClawBenchSource 18.2%Not comparable
Coding
BenchmarkGLM-5.1Trinity-Large-PreviewResult
SWE-bench ProSource 58.4%Not comparable
NL2RepoSource 42.7%Not comparable
SWE-RebenchSource 62.7%Not comparable
Vibe Code BenchSource 31.46%Not comparable
AA Coding IndexSource 55.8%Not comparable
AA-SciCodeSource 43.8%36.1%GLM-5.1 leads
Reasoning
BenchmarkGLM-5.1Trinity-Large-PreviewResult
AA-LCRSource 62.3%33.0%GLM-5.1 leads
CritPtSource 4.6%0.9%GLM-5.1 leads
Knowledge
BenchmarkGLM-5.1Trinity-Large-PreviewResult
GPQA-DSource 86.2%63.3%GLM-5.1 leads
HLESource 52.3%Not comparable
Artificial Analysis Intelligence IndexSource 40.2%24.5%GLM-5.1 leads
AA-GPQA DiamondSource 86.8%75.2%GLM-5.1 leads
AA-HLESource 28.0%14.7%GLM-5.1 leads
AA-Omniscience IndexSource 1.9%-44.2%GLM-5.1 leads
AA-Omniscience AccuracySource 24.2%22.8%GLM-5.1 leads
AA-Omniscience Hallucination RateSource 29.4%86.6%GLM-5.1 leads
MMLUSource 87.2%Not comparable
MMLU-Pro (Arcee)Source 75.2%Not comparable
Math
BenchmarkGLM-5.1Trinity-Large-PreviewResult
AIME26Source 95.3%Not comparable
HMMT Nov 2025Source 94.0%Not comparable
HMMT Feb 2026Source 82.6%Not comparable
MMAnswerBenchSource 83.8%Not comparable
FrontierMath v2 (Tiers 1-3)Source 33.448%Not comparable
FrontierMath v2 (Tier 4)Source 12.500%Not comparable
AIME25 (Arcee)Source 24.0%Not comparable
Multimodal
BenchmarkGLM-5.1Trinity-Large-PreviewResult
Design Arena WebsiteSource 13051165GLM-5.1 leads
Inst. Following
BenchmarkGLM-5.1Trinity-Large-PreviewResult
AA-IFBenchSource 76.3%56.3%GLM-5.1 leads
Frequently Asked Questions (3)

Can I compare GLM-5.1 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 GLM-5.1 and Trinity-Large-Preview today?

GLM-5.1: $1.40 input / $4.40 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.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

GLM-5.1
API / mo$4,350
Self-host / mo$18,221
Break-even264M/day
Trinity-Large-Preview
API / mo$938
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

Related Comparisons

Last updated: July 21, 2026

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.