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Model comparison

Claude Haiku 4.5 vs GLM-4.7

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.

56.58/100
Margin
4.6pts
winning →
61.16/100
1 category wins1 category wins

Public leaderboard positions: Claude Haiku 4.5 #77 (Estimated); GLM-4.7 #42 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Haiku 4.5 and GLM-4.7 share 4 comparable benchmark results. 2 of 8 categories are comparable. 1 result is unique to Claude Haiku 4.5; 26 to GLM-4.7.

Updated July 22, 2026
Shared results
4
Claude Haiku 4.5 only
1
GLM-4.7 only
26
Comparable categories
2 / 8

Pick GLM-4.7 if you want the stronger benchmark profile. Claude Haiku 4.5 only becomes the better choice if mathematics is the priority or you would rather avoid the extra latency and token burn of a reasoning model.

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, 61.16 to 56.58. 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 73.3. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 5.903% to 2.439%. Claude Haiku 4.5 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.

Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 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. GLM-4.7 is the reasoning model in the pair, while Claude Haiku 4.5 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.

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 Claude Haiku 4.5 and GLM-4.7
CategoryClaude Haiku 4.5ΔGLM-4.7
MathClaude Haiku 4.54.9Margin← 3.1GLM-4.71.8
CodingClaude Haiku 4.573.3Margin→ 2.1GLM-4.775.4
AgenticClaude Haiku 4.5Not measuredMarginNo overlapGLM-4.745.7
KnowledgeClaude Haiku 4.5Not measuredMarginNo overlapGLM-4.751.8

Decisive benchmark drivers

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

More
A · Claude Haiku 4.5B · GLM-4.7

  1. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 5.903%B 2.439%
    Winner: Claude Haiku 4.5Δ 3.5
    FrontierMath v2 (Tiers 1-3): Claude Haiku 4.5 scored 5.903%; GLM-4.7 scored 2.439%. Claude Haiku 4.5 wins this benchmark.

  2. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 2.083%B 0.000%
    Winner: Claude Haiku 4.5Δ 2.1
    FrontierMath v2 (Tier 4): Claude Haiku 4.5 scored 2.083%; GLM-4.7 scored 0.000%. Claude Haiku 4.5 wins this benchmark.

  3. SWE-bench Verified

    Coding
    Source ↗
    A 73.3%B 73.8%
    Winner: GLM-4.7Δ 0.5
    SWE-bench Verified: Claude Haiku 4.5 scored 73.3%; GLM-4.7 scored 73.8%. GLM-4.7 wins this benchmark.

Operational comparison

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

MetricClaude Haiku 4.5GLM-4.7Comparison
Input / output priceUSD per 1M tokensClaude Haiku 4.5$1 input / $5 outputGLM-4.7$0 input / $0 outputGLM-4.7 has the lower combined listed price.
Generation speedtokens per secondClaude Haiku 4.5Not availableGLM-4.782 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Haiku 4.5Not availableGLM-4.71.10 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Haiku 4.5200KGLM-4.7200KListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkClaude Haiku 4.5GLM-4.7Result
JobBenchSource 16.0%—Not comparable
Terminal-Bench 2.0Source —41%Not comparable
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%Not comparable
GDPval-AASource —33.3%Not comparable
GDPval-AASource —1165Not comparable
CodingGLM-4.7 wins
BenchmarkClaude Haiku 4.5GLM-4.7Result
SWE-bench VerifiedSource 73.3%73.8%GLM-4.7 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
Reasoning
BenchmarkClaude Haiku 4.5GLM-4.7Result
AA-LCRSource —64.0%Not comparable
CritPtSource —1.7%Not comparable
Knowledge
BenchmarkClaude Haiku 4.5GLM-4.7Result
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
MathClaude Haiku 4.5 wins
BenchmarkClaude Haiku 4.5GLM-4.7Result
FrontierMath v2 (Tiers 1-3)Source 5.903%2.439%Claude Haiku 4.5 leads
FrontierMath v2 (Tier 4)Source 2.083%0.000%Claude Haiku 4.5 leads
AIME 2025Source —95.7%Not comparable
Multimodal
BenchmarkClaude Haiku 4.5GLM-4.7Result
Design Arena WebsiteSource 11521255GLM-4.7 leads
Inst. Following
BenchmarkClaude Haiku 4.5GLM-4.7Result
AA-IFBenchSource —67.9%Not comparable
Frequently Asked Questions (3)

Which is better, Claude Haiku 4.5 or GLM-4.7?

GLM-4.7 is ahead on BenchLM's BenchAlign leaderboard, 61.16 to 56.58. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 5.903% and 2.439%.

Which is better for coding, Claude Haiku 4.5 or GLM-4.7?

GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 73.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for math, Claude Haiku 4.5 or GLM-4.7?

Claude Haiku 4.5 has the edge for math in this comparison, averaging 4.9 versus 1.8. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.

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