Which is better for coding — GLM-4.5 or K-EXAONE-236B-A23B?

Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.

Which model is cheaper — GLM-4.5 or K-EXAONE-236B-A23B?

GLM-4.5 is cheaper for input: $0.60 per 1M tokens vs $0.60.

Which has a larger context window — GLM-4.5 or K-EXAONE-236B-A23B?

GLM-4.5 supports a larger context: 131,072 tokens vs 32,768.

GLM-4.5 vs K-EXAONE-236B-A23B: Specs & Benchmark Comparison

Characteristic	GLM-4.5	K-EXAONE-236B-A23B
Company	Zhipu AI	LG AI Research
Release Date	July 27, 2025	December 30, 2025
Parameters	355B	236B
Multimodal	No	No
Context (input)	131K	33K
Context (output)	98K	33K
Input Price / 1M	$0.60	$0.60
Output Price / 1M	$2.20	$1.00
Average Score	0.8	0.8
Benchmarks
MMLU-Pro	0.8	0.8

Visual Benchmark Comparison

GLM-4.5

K-EXAONE-236B-A23B

MMLU-Pro0.8 vs 0.8

0.8

Verdict

K-EXAONE-236B-A23B leads in 2 out of 4 comparison categories.

Overall Performance

Both models show comparable average scores: GLM-4.5 — 0.8, K-EXAONE-236B-A23B — 0.8.

API Cost

K-EXAONE-236B-A23B is 1.8x cheaper: input $0.60/1M vs $0.60/1M tokens.

Context Window

GLM-4.5 supports a larger context: 131K vs 33K tokens.

Recency

K-EXAONE-236B-A23B is newer: released 12/30/2025 vs 7/27/2025.

More About These Models

GLM-4.5

Zhipu AI — specs, benchmarks, API

K-EXAONE-236B-A23B

LG AI Research — specs, benchmarks, API

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The GLM-4.5 and K-EXAONE-236B-A23B comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the GLM-4.5 or K-EXAONE-236B-A23B page. See also the complete list of AI model comparisons.