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Model comparison

GLM-4.7 vs Grok 4.20

Data verified

Head-to-head evidence from 4 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

60.39/100
Margin
6.5pts
← winning
53.88/100
1 category wins1 category wins

Public leaderboard positions: GLM-4.7 #46 (Supported); Grok 4.20 #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GLM-4.7 and Grok 4.20 share 4 comparable benchmark results. 2 of 8 categories are comparable. 26 results are unique to GLM-4.7; 15 to Grok 4.20.

Updated July 28, 2026
Shared results
4
GLM-4.7 only
26
Grok 4.20 only
15
Comparable categories
2 / 8

Pick GLM-4.7 if you want the stronger benchmark profile. Grok 4.20 only becomes the better choice if agentic is the priority or you need the larger 2M context window.

Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 3 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-4.7 is clearly ahead on the BenchAlign aggregate, 60.39 to 53.88. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GLM-4.7's sharpest advantage is in coding, where it averages 75.4 against 67.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 41% to 47.1%. Grok 4.20 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.

Grok 4.20 is also the more expensive model on tokens at $2.00 input / $6.00 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. Grok 4.20 gives you the larger context window at 2M, 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 Grok 4.20
CategoryGLM-4.7ΔGrok 4.20
CodingGLM-4.775.4Margin← 8.3Grok 4.2067.1
AgenticGLM-4.745.7Margin→ 1.4Grok 4.2047.1
ReasoningGLM-4.7Not measuredMarginNo overlapGrok 4.2053.3
KnowledgeGLM-4.751.8MarginNo overlapGrok 4.20Not measured
MathGLM-4.71.8MarginNo overlapGrok 4.20Not measured
MultimodalGLM-4.7Not measuredMarginNo overlapGrok 4.2070.1

Decisive benchmark drivers

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

More
A · GLM-4.7B · Grok 4.20

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 41%B 47.1%
    Winner: Grok 4.20Δ 6.1
    Terminal-Bench 2.0: GLM-4.7 scored 41%; Grok 4.20 scored 47.1%. Grok 4.20 wins this benchmark.

  2. SWE-bench Verified

    Coding
    Source ↗
    A 73.8%B 76.7%
    Winner: Grok 4.20Δ 2.9
    SWE-bench Verified: GLM-4.7 scored 73.8%; Grok 4.20 scored 76.7%. Grok 4.20 wins this benchmark.

Operational comparison

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

MetricGLM-4.7Grok 4.20Comparison
Input / output priceUSD per 1M tokensGLM-4.7$0 input / $0 outputGrok 4.20$2 input / $6 outputGLM-4.7 has the lower combined listed price.
Generation speedtokens per secondGLM-4.782 tok/sGrok 4.20233 tok/sGrok 4.20 has the higher measured throughput.
First-answer latencyseconds to first tokenGLM-4.71.10 sGrok 4.2010.33 sGLM-4.7 reaches the first token sooner.
Context windowmaximum listed tokensGLM-4.7200KGrok 4.202MGrok 4.20 lists the larger context window.

Benchmark Deep Dive

AgenticGrok 4.20 wins
BenchmarkGLM-4.7Grok 4.20Result
Terminal-Bench 2.0Source 41%47.1%Grok 4.20 leads
BrowseCompSource 52%—Not comparable
VITA-BenchSource 15.5%—Not comparable
AA Agentic IndexSource 25.4%—Not comparable
τ²-bench resultsSource 95.9%—Not comparable
Gert LabsSource 39.95%38.36%GLM-4.7 leads
GDPval-AASource 33.3%—Not comparable
GDPval-AASource 1166—Not comparable
DeepSearchQASource —62.8%Not comparable
CodingGLM-4.7 wins
BenchmarkGLM-4.7Grok 4.20Result
SWE-bench VerifiedSource 73.8%76.7%Grok 4.20 leads
LiveCodeBenchSource 84.9%—Not comparable
SWE-RebenchSource 58.7%—Not comparable
AA Coding IndexSource 45.3%—Not comparable
AA-SciCodeSource 45.1%—Not comparable
AA LiveCodeBenchSource 89.4%—Not comparable
LiveCodeBench ProSource —74.2%Not comparable
SWE-bench ProSource —51.8%Not comparable
Vibe Code BenchSource —4.06%Not comparable
Reasoning
BenchmarkGLM-4.7Grok 4.20Result
AA-LCRSource 64.0%—Not comparable
CritPtSource 1.7%—Not comparable
ARC-AGI-2Source —53.3%Not comparable
ARC-AGI-3Source —0.1%Not comparable
Knowledge
BenchmarkGLM-4.7Grok 4.20Result
GPQASource 85.7%—Not comparable
MMLU-ProSource 84.3%—Not comparable
HLESource 24.8%—Not comparable
Artificial Analysis Intelligence IndexSource 33.7%—Not comparable
AA-GPQA DiamondSource 85.9%—Not comparable
AA-HLESource 25.1%—Not comparable
AA-Omniscience IndexSource -34.6%—Not comparable
AA-Omniscience AccuracySource 29.3%—Not comparable
AA-Omniscience Hallucination RateSource 90.3%—Not comparable
GPQA-DSource —88.5%Not comparable
HLE w/o toolsSource —31.6%Not comparable
HealthBench HardSource —20.3%Not comparable
MedXpertQA (Text)Source —50.2%Not comparable
Math
BenchmarkGLM-4.7Grok 4.20Result
AIME 2025Source 95.7%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 2.439%—Not comparable
FrontierMath v2 (Tier 4)Source 0.000%—Not comparable
Multimodal
BenchmarkGLM-4.7Grok 4.20Result
Design Arena WebsiteSource 12511252Grok 4.20 leads
MMMU-ProSource —75.2%Not comparable
CharXivSource —60.9%Not comparable
ERQASource —54.1%Not comparable
SimpleVQASource —57.4%Not comparable
MedXpertQA (MM)Source —65.8%Not comparable
Inst. Following
BenchmarkGLM-4.7Grok 4.20Result
AA-IFBenchSource 67.9%—Not comparable
Frequently Asked Questions (3)

Which is better, GLM-4.7 or Grok 4.20?

GLM-4.7 is ahead on BenchLM's BenchAlign leaderboard, 60.39 to 53.88. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 41% and 47.1%.

Which is better for coding, GLM-4.7 or Grok 4.20?

GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 67.1. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, GLM-4.7 or Grok 4.20?

Grok 4.20 has the edge for agentic tasks in this comparison, averaging 47.1 versus 45.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

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