Skip to main content
BenchLM
Advertise

Model comparison

GLM-4.7 vs GPT-5.2

Data verified

Head-to-head evidence from 18 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

61.16/100
Margin
2.7pts
← winning
GPT-5.2
OpenAI
58.43/100
1 category wins3 category wins

Public leaderboard positions: GLM-4.7 #42 (Supported); GPT-5.2 #64 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-4.7 and GPT-5.2 share 18 comparable benchmark results. 4 of 8 categories are comparable. 12 results are unique to GLM-4.7; 10 to GPT-5.2.

Updated July 20, 2026
Shared results
18
GLM-4.7 only
12
GPT-5.2 only
10
Comparable categories
4 / 8

Pick GLM-4.7 if you want the stronger benchmark profile. GPT-5.2 only becomes the better choice if knowledge is the priority or you need the larger 400K context window.

Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 7 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

GLM-4.7 has the cleaner BenchAlign overall profile here, landing at 61.16 versus 58.43. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

GLM-4.7's sharpest advantage is in coding, where it averages 75.4 against 70.6. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 2.439% to 40.700%. GPT-5.2 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. That is roughly Infinityx on output cost alone. GPT-5.2 gives you the larger context window at 400K, compared with 200K for GLM-4.7.

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-4.7 and GPT-5.2
CategoryGLM-4.7ΔGPT-5.2
KnowledgeGLM-4.751.8Margin→ 40.6GPT-5.292.4
MathGLM-4.71.8Margin→ 33.4GPT-5.235.2
AgenticGLM-4.745.7Margin→ 10.0GPT-5.255.7
CodingGLM-4.775.4Margin← 4.8GPT-5.270.6
ReasoningGLM-4.7Not measuredMarginNo overlapGPT-5.252.9
MultimodalGLM-4.7Not measuredMarginNo overlapGPT-5.280.4

Decisive benchmark drivers

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

More
A · GLM-4.7B · GPT-5.2

  1. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 2.439%B 40.700%
    Winner: GPT-5.2Δ 38.3
    FrontierMath v2 (Tiers 1-3): GLM-4.7 scored 2.439%; GPT-5.2 scored 40.700%. GPT-5.2 wins this benchmark.

  2. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 0.000%B 18.800%
    Winner: GPT-5.2Δ 18.8
    FrontierMath v2 (Tier 4): GLM-4.7 scored 0.000%; GPT-5.2 scored 18.800%. GPT-5.2 wins this benchmark.

  3. BrowseComp

    Agentic
    Source ↗
    A 52%B 65.8%
    Winner: GPT-5.2Δ 13.8
    BrowseComp: GLM-4.7 scored 52%; GPT-5.2 scored 65.8%. GPT-5.2 wins this benchmark.

  4. GPQA

    Knowledge
    Source ↗
    A 85.7%B 92.4%
    Winner: GPT-5.2Δ 6.7
    GPQA: GLM-4.7 scored 85.7%; GPT-5.2 scored 92.4%. GPT-5.2 wins this benchmark.

  5. SWE-bench Verified

    Coding
    Source ↗
    A 73.8%B 80%
    Winner: GPT-5.2Δ 6.2
    SWE-bench Verified: GLM-4.7 scored 73.8%; GPT-5.2 scored 80%. GPT-5.2 wins this benchmark.

Operational comparison

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

MetricGLM-4.7GPT-5.2Comparison
Input / output priceUSD per 1M tokensGLM-4.7$0 input / $0 outputGPT-5.2$1.75 input / $14 outputGLM-4.7 has the lower combined listed price.
Generation speedtokens per secondGLM-4.782 tok/sGPT-5.273 tok/sGLM-4.7 has the higher measured throughput.
First-answer latencyseconds to first tokenGLM-4.71.10 sGPT-5.2130.34 sGLM-4.7 reaches the first token sooner.
Context windowmaximum listed tokensGLM-4.7200KGPT-5.2400KGPT-5.2 lists the larger context window.

Benchmark Deep Dive

AgenticGPT-5.2 wins
BenchmarkGLM-4.7GPT-5.2Result
Terminal-Bench 2.0Source 41%—Not comparable
BrowseCompSource 52%65.8%GPT-5.2 leads
VITA-BenchSource 15.5%—Not comparable
AA Agentic IndexSource 25.4%—Not comparable
τ²-bench resultsSource 95.9%84.8%GLM-4.7 leads
Gert LabsSource 39.95%46.54%GPT-5.2 leads
GDPval-AASource 33.3%—Not comparable
GDPval-AASource 1165—Not comparable
OSWorld-VerifiedSource —47.3%Not comparable
JobBenchSource —34.3%Not comparable
CodingGLM-4.7 wins
BenchmarkGLM-4.7GPT-5.2Result
SWE-bench VerifiedSource 73.8%80%GPT-5.2 leads
LiveCodeBenchSource 84.9%—Not comparable
SWE-RebenchSource 58.7%—Not comparable
AA Coding IndexSource 45.3%—Not comparable
AA-SciCodeSource 45.1%52.1%GPT-5.2 leads
AA LiveCodeBenchSource 89.4%—Not comparable
SWE-bench ProSource —55.6%Not comparable
Vibe Code BenchSource —53.50%Not comparable
Reasoning
BenchmarkGLM-4.7GPT-5.2Result
AA-LCRSource 64.0%72.7%GPT-5.2 leads
CritPtSource 1.7%11.6%GPT-5.2 leads
ARC-AGI-2Source —52.9%Not comparable
KnowledgeGPT-5.2 wins
BenchmarkGLM-4.7GPT-5.2Result
GPQASource 85.7%92.4%GPT-5.2 leads
MMLU-ProSource 84.3%—Not comparable
HLESource 24.8%—Not comparable
Artificial Analysis Intelligence IndexSource 33.7%42.2%GPT-5.2 leads
AA-GPQA DiamondSource 85.9%90.3%GPT-5.2 leads
AA-HLESource 25.1%35.4%GPT-5.2 leads
AA-Omniscience IndexSource -34.6%-1.0%GPT-5.2 leads
AA-Omniscience AccuracySource 29.3%43.8%GPT-5.2 leads
AA-Omniscience Hallucination RateSource 90.3%79.7%GPT-5.2 leads
MathGPT-5.2 wins
BenchmarkGLM-4.7GPT-5.2Result
AIME 2025Source 95.7%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 2.439%40.700%GPT-5.2 leads
FrontierMath v2 (Tier 4)Source 0.000%18.800%GPT-5.2 leads
AA AIME 2025Source —99.0%Not comparable
Multimodal
BenchmarkGLM-4.7GPT-5.2Result
Design Arena WebsiteSource 12581227GLM-4.7 leads
MMMU-ProSource —79.5%Not comparable
MathVisionSource —83.0%Not comparable
CharXivSource —82.1%Not comparable
V*Source —75.9%Not comparable
Inst. Following
BenchmarkGLM-4.7GPT-5.2Result
AA-IFBenchSource 67.9%75.4%GPT-5.2 leads
Frequently Asked Questions (5)

Which is better, GLM-4.7 or GPT-5.2?

GLM-4.7 is ahead on BenchLM's BenchAlign leaderboard, 61.16 to 58.43. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 2.439% and 40.700%.

Which is better for knowledge tasks, GLM-4.7 or GPT-5.2?

GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 51.8. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for coding, GLM-4.7 or GPT-5.2?

GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 70.6. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.

Which is better for math, GLM-4.7 or GPT-5.2?

GPT-5.2 has the edge for math in this comparison, averaging 35.2 versus 1.8. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GLM-4.7 or GPT-5.2?

GPT-5.2 has the edge for agentic tasks in this comparison, averaging 55.7 versus 45.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.

Related Comparisons

Explore More

Z.AI Compare Pricing Methodology Find Your Best LLM Overall Rankings
Last updated: July 20, 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.