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Model comparison

GLM-4.7 vs Interfaze Beta

Data verified

Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use BenchLM's provisional ranking lane.

62/100
Margin
1.0pts
winning →
63/100
0 category wins1 category wins

Verified leaderboard positions: GLM-4.7 #32; Interfaze Beta unranked

Evidence parity. GLM-4.7 and Interfaze Beta share 1 comparable benchmark result. 1 of 8 categories are comparable. 30 results are unique to GLM-4.7; 9 to Interfaze Beta.

Updated July 14, 2026
Shared results
1
GLM-4.7 only
30
Interfaze Beta only
9
Comparable categories
1 / 8

Pick Interfaze Beta if you want the stronger benchmark profile. GLM-4.7 only becomes the better choice if you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Interfaze Beta finishes one point ahead on BenchLM's provisional leaderboard, 63 to 62. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.

Interfaze Beta's sharpest advantage is in knowledge, where it averages 89.9 against 52.1. The single biggest benchmark swing on the page is GPQA, 85.7% to 89.9%.

Interfaze Beta is also the more expensive model on tokens at $1.50 input / $3.50 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. Interfaze Beta gives you the larger context window at 1M, 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 Interfaze Beta
CategoryGLM-4.7ΔInterfaze Beta
KnowledgeGLM-4.752.1Margin 37.8Interfaze Beta89.9
AgenticGLM-4.745.7MarginNo overlapInterfaze BetaNot measured
CodingGLM-4.773.8MarginNo overlapInterfaze BetaNot measured
MathGLM-4.71.8MarginNo overlapInterfaze BetaNot measured
MultimodalGLM-4.7Not measuredMarginNo overlapInterfaze Beta71.1

Decisive benchmark drivers

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

More
A · GLM-4.7B · Interfaze Beta
  1. GPQA

    Knowledge
    Source ↗
    A 85.7%B 89.9%
    Winner: Interfaze BetaΔ 4.2
    GPQA: GLM-4.7 scored 85.7%; Interfaze Beta scored 89.9%. Interfaze Beta wins this benchmark.

Operational comparison

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

MetricGLM-4.7Interfaze BetaComparison
Input / output priceUSD per 1M tokensGLM-4.7$0 input / $0 outputInterfaze Beta$1.5 input / $3.5 outputGLM-4.7 has the lower combined listed price.
Generation speedtokens per secondGLM-4.782 tok/sInterfaze BetaNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGLM-4.71.10 sInterfaze BetaNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGLM-4.7200KInterfaze Beta1MInterfaze Beta lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGLM-4.7Interfaze BetaResult
Terminal-Bench 2.0Source 41%Not comparable
BrowseCompSource 52%Not comparable
VITA-BenchSource 15.5%Not comparable
AA Agentic IndexSource 25.4%Not comparable
Tau2-TelecomSource 95.9%Not comparable
Gert LabsSource 39.95%Not comparable
GDPval-AASource 33.3%Not comparable
GDPval-AASource 1165Not comparable
Coding
BenchmarkGLM-4.7Interfaze BetaResult
SWE-bench VerifiedSource 73.8%Not comparable
LiveCodeBenchSource 84.9%Not comparable
SWE-RebenchSource 58.7%Not comparable
AA Coding IndexSource 45.3%Not comparable
Terminal-Bench HardSource 31.8%Not comparable
AA-SciCodeSource 45.1%Not comparable
AA LiveCodeBenchSource 89.4%Not comparable
Spider 2.0-LiteSource 52.9%Not comparable
Reasoning
BenchmarkGLM-4.7Interfaze BetaResult
AA-LCRSource 64.0%Not comparable
CritPtSource 1.7%Not comparable
KnowledgeInterfaze Beta wins
BenchmarkGLM-4.7Interfaze BetaResult
GPQASource 85.7%89.9%Interfaze Beta leads
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 89.9%Not comparable
MMMLUSource 90.9%Not comparable
Math
BenchmarkGLM-4.7Interfaze BetaResult
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-4.7Interfaze BetaResult
Design Arena WebsiteSource 1260Not comparable
OCRBench V2Source 70.7%Not comparable
olmOCRSource 85.7%Not comparable
RefCOCO (avg)Source 82.1%Not comparable
VoxPopuli WERSource 2.4%Not comparable
MMMU-ProSource 71.1%Not comparable
Inst. Following
BenchmarkGLM-4.7Interfaze BetaResult
AA-IFBenchSource 67.9%Not comparable
SOB Value AccSource 79.5%Not comparable
Frequently Asked Questions (2)

Which is better, GLM-4.7 or Interfaze Beta?

Interfaze Beta is ahead on BenchLM's provisional leaderboard, 63 to 62. The biggest single separator in this matchup is GPQA, where the scores are 85.7% and 89.9%.

Which is better for knowledge tasks, GLM-4.7 or Interfaze Beta?

Interfaze Beta has the edge for knowledge tasks in this comparison, averaging 89.9 versus 52.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.

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Last updated: July 14, 2026

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