Model comparison

GLM-4.7 vs ZAYA1-8B

Data verified July 14, 2026

Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use BenchLM's provisional ranking lane.

GLM-4.7

Z.AI

62/100

Margin

7.0pts

← winning

ZAYA1-8B

Zyphra

55/100

0 category wins2 category wins

Verified leaderboard positions: GLM-4.7 #32; ZAYA1-8B unranked

Evidence parity. GLM-4.7 and ZAYA1-8B share 2 comparable benchmark results. 2 of 8 categories are comparable. 29 results are unique to GLM-4.7; 9 to ZAYA1-8B.

Updated July 14, 2026

Shared results: 2
GLM-4.7 only: 29
ZAYA1-8B only: 9
Comparable categories: 2 / 8

Pick GLM-4.7 if you want the stronger benchmark profile. ZAYA1-8B only becomes the better choice if mathematics is the priority.

Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 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 provisional aggregate, 62 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

GLM-4.7 gives you the larger context window at 200K, compared with 131K for ZAYA1-8B.

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 ZAYA1-8B
Category	GLM-4.7	Δ	ZAYA1-8B
Math	GLM-4.71.8	Margin→ 78.6	ZAYA1-8B80.4
Knowledge	GLM-4.752.1	Margin→ 21.5	ZAYA1-8B73.6
Agentic	GLM-4.745.7	MarginNo overlap	ZAYA1-8BNot measured
Coding	GLM-4.773.8	MarginNo overlap	ZAYA1-8BNot measured
Inst. Following	GLM-4.7Not measured	MarginNo overlap	ZAYA1-8B64.1

Decisive benchmark drivers

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

A · GLM-4.7B · ZAYA1-8B

GPQA
Knowledge
Source ↗
A 85.7%B 71%
Winner: GLM-4.7Δ 14.7
GPQA: GLM-4.7 scored 85.7%; ZAYA1-8B scored 71%. GLM-4.7 wins this benchmark.
MMLU-Pro
Knowledge
Source ↗
A 84.3%B 74.2%
Winner: GLM-4.7Δ 10.1
MMLU-Pro: GLM-4.7 scored 84.3%; ZAYA1-8B scored 74.2%. GLM-4.7 wins this benchmark.

Operational comparison

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

Metric	GLM-4.7	ZAYA1-8B	Comparison
Input / output priceUSD per 1M tokens	GLM-4.7$0 input / $0 output	ZAYA1-8B$0 input / $0 output	Listed prices are equal.
Generation speedtokens per second	GLM-4.782 tok/s	ZAYA1-8BNot available	A complete speed comparison is not available.
First-answer latencyseconds to first token	GLM-4.71.10 s	ZAYA1-8BNot available	A complete latency comparison is not available.
Context windowmaximum listed tokens	GLM-4.7200K	ZAYA1-8B131K	GLM-4.7 lists the larger context window.

Benchmark Deep Dive

Agentic

9 benchmarks

Benchmark	GLM-4.7	ZAYA1-8B	Result
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	1165	—	Not comparable
BFCL v4Source	—	39.2%	Not comparable

Coding

8 benchmarks

Benchmark	GLM-4.7	ZAYA1-8B	Result
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
LiveCodeBench v6Source	—	65.8%	Not comparable

Reasoning

2 benchmarks

Benchmark	GLM-4.7	ZAYA1-8B	Result
AA-LCRSource	64.0%	—	Not comparable
CritPtSource	1.7%	—	Not comparable

KnowledgeZAYA1-8B wins

10 benchmarks

Benchmark	GLM-4.7	ZAYA1-8B	Result
GPQASource	85.7%	71%	GLM-4.7 leads
MMLU-ProSource	84.3%	74.2%	GLM-4.7 leads
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	—	71.0%	Not comparable

MathZAYA1-8B wins

7 benchmarks

Benchmark	GLM-4.7	ZAYA1-8B	Result
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
AIME26Source	—	89.1%	Not comparable
HMMT Feb 2026Source	—	71.6%	Not comparable
IMOAnswerBenchSource	—	59.3%	Not comparable
ApexSource	—	32.2%	Not comparable

Multimodal

1 benchmarks

Benchmark	GLM-4.7	ZAYA1-8B	Result
Design Arena WebsiteSource	1260	—	Not comparable

Inst. Following

3 benchmarks

Benchmark	GLM-4.7	ZAYA1-8B	Result
AA-IFBenchSource	67.9%	—	Not comparable
IFEvalSource	—	85.6%	Not comparable
IFBenchSource	—	52.6%	Not comparable

Frequently Asked Questions (3)

Which is better, GLM-4.7 or ZAYA1-8B?

GLM-4.7 is ahead on BenchLM's provisional leaderboard, 62 to 55. The biggest single separator in this matchup is GPQA, where the scores are 85.7% and 71%.

Which is better for knowledge tasks, GLM-4.7 or ZAYA1-8B?

ZAYA1-8B has the edge for knowledge tasks in this comparison, averaging 73.6 versus 52.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for math, GLM-4.7 or ZAYA1-8B?

ZAYA1-8B has the edge for math in this comparison, averaging 80.4 versus 1.8. GLM-4.7 stays close enough that the answer can still flip depending on your workload.

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Last updated: July 14, 2026

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