Model comparison

GLM-5 vs Laguna XS.2

Data verified July 27, 2026

Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

GLM-5

Z.AI

65.24/100

No comparison

Laguna XS.2

Poolside

N/A

2 category wins0 category wins

Public leaderboard positions: GLM-5 #31 (Supported); Laguna XS.2 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-5 and Laguna XS.2 share 4 comparable benchmark results. 2 of 8 categories are comparable. 45 results are unique to GLM-5; 1 to Laguna XS.2.

Updated July 27, 2026

Shared results: 4
GLM-5 only: 45
Laguna XS.2 only: 1
Comparable categories: 2 / 8

Treat this as a split decision. GLM-5 makes more sense if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model; Laguna XS.2 is the better fit if you want the cheaper token bill or you need the larger 256K context window.

Confidence note. This is a partial-evidence comparison with 4 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

GLM-5 and Laguna XS.2 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.

GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Laguna XS.2. That is roughly Infinityx on output cost alone. Laguna XS.2 is the reasoning model in the pair, while GLM-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 XS.2 gives you the larger context window at 256K, compared with 200K for GLM-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 GLM-5 and Laguna XS.2
Category	GLM-5	Δ	Laguna XS.2
Agentic	GLM-556.2	Margin← 20.5	Laguna XS.235.7
Coding	GLM-566.3	Margin← 5.5	Laguna XS.260.8
Reasoning	GLM-560.8	MarginNo overlap	Laguna XS.2Not measured
Knowledge	GLM-566.4	MarginNo overlap	Laguna XS.2Not measured
Math	GLM-556.3	MarginNo overlap	Laguna XS.2Not measured
Multilingual	GLM-583.1	MarginNo overlap	Laguna XS.2Not measured
Inst. Following	GLM-592.6	MarginNo overlap	Laguna XS.2Not measured

Decisive benchmark drivers

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

A · GLM-5B · Laguna XS.2

Terminal-Bench 2.0
Agentic
Source ↗
A 56.2%B 35.7%
Winner: GLM-5Δ 20.5
Terminal-Bench 2.0: GLM-5 scored 56.2%; Laguna XS.2 scored 35.7%. GLM-5 wins this benchmark.
SWE-bench Pro
Coding
Source ↗
A 55.1%B 46.3%
Winner: GLM-5Δ 8.8
SWE-bench Pro: GLM-5 scored 55.1%; Laguna XS.2 scored 46.3%. GLM-5 wins this benchmark.
SWE-bench Verified
Coding
Source ↗
A 77.8%B 69.9%
Winner: GLM-5Δ 7.9
SWE-bench Verified: GLM-5 scored 77.8%; Laguna XS.2 scored 69.9%. GLM-5 wins this benchmark.

Operational comparison

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

Metric	GLM-5	Laguna XS.2	Comparison
Input / output priceUSD per 1M tokens	GLM-5$1 input / $3.2 output	Laguna XS.2$0 input / $0 output	Laguna XS.2 has the lower combined listed price.
Generation speedtokens per second	GLM-574 tok/s	Laguna XS.2Not available	A complete speed comparison is not available.
First-answer latencyseconds to first token	GLM-51.64 s	Laguna XS.2Not available	A complete latency comparison is not available.
Context windowmaximum listed tokens	GLM-5200K	Laguna XS.2256K	Laguna XS.2 lists the larger context window.

Benchmark Deep Dive

AgenticGLM-5 wins

13 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
Terminal-Bench 2.0Source	56.2%	35.7%	GLM-5 leads
Claw-EvalSource	57.7%	—	Not comparable
QwenClawBenchSource	54.1%	—	Not comparable
τ³-bench resultsSource	65.6%	—	Not comparable
DeepPlanningSource	14.6%	—	Not comparable
ToolathlonSource	38%	—	Not comparable
MCP AtlasSource	31.1%	—	Not comparable
MCP-TasksSource	60.8%	—	Not comparable
WideResearchSource	69.8%	—	Not comparable
τ²-bench resultsSource	98.2%	—	Not comparable
CyberGymSource	43.2%	—	Not comparable
APEX-Agents-AASource	14.5%	—	Not comparable
Gert LabsSource	50.99%	—	Not comparable

CodingGLM-5 wins

8 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
SWE-bench VerifiedSource	77.8%	69.9%	GLM-5 leads
SWE-bench Verified*Source	72.8%	—	Not comparable
SWE-bench ProSource	55.1%	46.3%	GLM-5 leads
SWE MultilingualSource	73.3%	57.7%	GLM-5 leads
SWE-RebenchSource	62.8%	—	Not comparable
React Native EvalsSource	74.8%	—	Not comparable
AA-SciCodeSource	46.2%	—	Not comparable
Terminal-Bench 2.0Source	—	35.7%	Not comparable

Reasoning

4 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
LongBench v2Source	60.8%	—	Not comparable
AI-NeedleSource	63.3%	—	Not comparable
AA-LCRSource	63.3%	—	Not comparable
CritPtSource	2.0%	—	Not comparable

Knowledge

12 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
GPQASource	86%	—	Not comparable
GPQA-DSource	86.0%	—	Not comparable
SuperGPQASource	66.8%	—	Not comparable
MMLU-ProSource	85.7%	—	Not comparable
MMLU-Pro (Arcee)Source	85.8%	—	Not comparable
HLESource	50.4%	—	Not comparable
Artificial Analysis Intelligence IndexSource	39.5%	—	Not comparable
AA-GPQA DiamondSource	82.0%	—	Not comparable
AA-HLESource	27.2%	—	Not comparable
AA-Omniscience IndexSource	2.0%	—	Not comparable
AA-Omniscience AccuracySource	26.9%	—	Not comparable
AA-Omniscience Hallucination RateSource	34.0%	—	Not comparable

Math

8 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
AIME26Source	95.8%	—	Not comparable
AIME25 (Arcee)Source	93.3%	—	Not comparable
HMMT Feb 2025Source	97.5%	—	Not comparable
HMMT Nov 2025Source	96.9%	—	Not comparable
HMMT Feb 2026Source	86.4%	—	Not comparable
MMAnswerBenchSource	82.5%	—	Not comparable
FrontierMath v2 (Tiers 1-3)Source	16.434%	—	Not comparable
FrontierMath v2 (Tier 4)Source	2.100%	—	Not comparable

Multilingual

2 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
MMLU-ProXSource	83.1%	—	Not comparable
NOVA-63Source	55.1%	—	Not comparable

Multimodal

1 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
Design Arena WebsiteSource	1274	—	Not comparable

Inst. Following

2 benchmarks

Benchmark	GLM-5	Laguna XS.2	Result
IFEvalSource	92.6%	—	Not comparable
AA-IFBenchSource	72.3%	—	Not comparable

Frequently Asked Questions (3)

Which is better, GLM-5 or Laguna XS.2?

GLM-5 and Laguna XS.2 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, GLM-5 or Laguna XS.2?

GLM-5 has the edge for coding in this comparison, averaging 66.3 versus 60.8. Inside this category, SWE Multilingual is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GLM-5 or Laguna XS.2?

GLM-5 has the edge for agentic tasks in this comparison, averaging 56.2 versus 35.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

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