GPT-4.1 vs GLM 5.2

OpenAI

68#143

Zhipu AI

69#136

Signal-by-Signal Comparison

Signal	GPT-4.1	Delta	GLM 5.2
Capabilities	83	+17	67
Benchmarks	70	+2	69
Pricing	92	-1	93
Context window size	96	--	96
Recency	31	-69	100
Output Capacity	72	-23	96
Overall Result	2 wins	of 6	3 wins

GLM 5.2 wins 3 of 6 signals

Score History

Score History (37 data points)

GPT-4.1GLM 5.2

GPT-4.1

67.7

current score

Leader

GLM 5.2

right now

GLM 5.2

68.9

current score

LMMarketCap.com

Interactive Price Comparison

Quick presets

Monthly API calls

100Kcalls/month

Avg. input tokens/call

1,000tokens (~1,333 chars)

Avg. output tokens/call

500tokens (~667 chars)

GPT-4.1

OpenAI

Per request$0.006000

Daily$20.00

Monthly$600.00

Annual$7200.00

GLM 5.2

Zhipu AI

Best Value

Per request$0.003534

Daily$11.78

Monthly$353.41

Annual$4240.92

GLM 5.2 saves you $246.59/month

That's $2959.08/year compared to GPT-4.1 at your current usage level of 100K calls/month.

41% cheaper

Choose GLM 5.2 for cost optimization

GPT-4.1 pricing:

Input:$2.00/M tokens

Output:$8.00/M tokens

GLM 5.2 pricing:

Input:$0.03/M tokens

Output:$7.00/M tokens

GPT-4.1

OpenAI

Composite Score

Winner

GLM 5.2

Zhipu AI

Composite Score

Signal-by-Signal Comparison

Metric	GPT-4.1	GLM 5.2	Winner
Overall Score	68	69	GLM 5.2
Rank	#143	#136	GLM 5.2
Quality Rank	#143	#136	GLM 5.2
Adoption Rank	#143	#136	GLM 5.2
Parameters	--	--	--
Context Window	1048K	1049K	GLM 5.2
Pricing	$2.00/$8.00/M	$0.03/$7.00/M	--
Signal Scores
Capabilities	83	67	GPT-4.1
Benchmarks	70	69	GPT-4.1
Pricing	92	93	GLM 5.2
Context window size	96	96	GPT-4.1
Recency	31	100	GLM 5.2
Output Capacity	72	96	GLM 5.2

Benchmark Head-to-Head(12 benchmarks)

GPT-4.1: 0GLM 5.2: 1

GPT-4.1

GLM 5.2

Normalized 0-100%

MMLU

89.2%-

MMLU-Pro

81.8%86%

GPQA Diamond

56%-

MATH-500

78.5%-

HumanEval

91.5%-

SWE-bench Verified

54.6%-

IFEval

88.2%-

BBH

84%-

Arena Elo

1300-

LiveBench

64.5%-

HLE

5.4%-

BigCodeBench

31.8%-

Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

GPT-4.1Competitive

Scores 68/100 (rank #143), placing it in the top 51% of all 290 models tracked.

Raw Quality0/100

Cost Efficiency0/100

Speed0/100

GLM 5.2Competitive

Scores 69/100 (rank #136), placing it in the top 53% of all 290 models tracked.

Raw Quality0/100

Cost Efficiency0/100

Speed0/100

With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose GPT-4.1 when you need:

Multimodal workflows that require image understanding

Choose GLM 5.2 when you need:

Step-by-step reasoning and chain-of-thought problem solving
Self-hosted deployments where you need full control over the model

Cost-Performance Analysis

GPT-4.1

Input cost$2.00/M tokens

Output cost$8.00/M tokens

Cost per quality point$0.148

Est. monthly (1M tokens/day)$150.00

GLM 5.2Best Value

Input cost$0.03/M tokens

Output cost$7.00/M tokens

Cost per quality point$0.102

Est. monthly (1M tokens/day)$105.51

GLM 5.2 offers 30% better value per quality point. At 1M tokens/day, you'd spend $105.51/month with GLM 5.2 vs $150.00/month with GPT-4.1 - a $44.49 monthly difference.

Latency & Speed

GPT-4.1Faster

Speed score0/100

GLM 5.2

Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

GPT-4.1

Customer support chatbot

Suitable for user-facing chat with competitive response times. GLM 5.2 also offers lower per-token costs for high-volume support

GPT-4.1

Long document analysis

Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass

GLM 5.2

Batch data extraction

Lower output pricing ($7.00/M) reduces costs when processing thousands of records daily

GLM 5.2

Creative writing & content

Higher overall composite score (69/100) correlates with better nuance, coherence, and style in long-form content

GLM 5.2

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

GPT-4.1

Which Should You Choose?

Our recommendation:

GLM 5.2

GPT-4.1 and GLM 5.2 are extremely close in overall performance (only 1.2000000000000028 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

By Use Case

Best for Quality

GPT-4.1

Marginally better benchmark scores; both are excellent

Best for Cost

GLM 5.2

30% lower pricing; better value at scale

Best for Reliability

GPT-4.1

Higher uptime and faster response speeds

Best for Prototyping

GPT-4.1

Stronger community support and better developer experience

Best for Production

GPT-4.1

Wider enterprise adoption and proven at scale

GPT-4.1

by OpenAI

Choose for Quality - Marginally better benchmark scores; both are excellent
Choose for Reliability - Higher uptime and faster response speeds
Choose for Prototyping - Stronger community support and better developer experience
Choose for Production - Wider enterprise adoption and proven at scale