Popular Comparisons:
Zhipu AIVerified

GLM-4-Flash

Input$0 / 1M
Output$0 / 1M
Context128K
CursorBench Pass Rate—
Zhipu AIVerified

GLM-5.1

Input$1.40 / 1M
Output$4.40 / 1M
Context128K
CursorBench Pass Rate—
Zhipu AIVerified

GLM-5.2

Input$1.40 / 1M
Output$4.40 / 1M
Context256K
CursorBench Pass Rate—

Pick your workflow, then your budget

Estimates use our price snapshot, excluding cache, retries, taxes and tools. Check availability for preview and legacy models.

Workload cost · USD (lower costs less)

GLM-4-Flash$0.00
GLM-5.1$22.80
GLM-5.2$22.80

Context capacity · tokens (not recall accuracy)

GLM-4-Flash128,000
GLM-5.1128,000
GLM-5.2256,000

CursorBench 4.0 · %

GLM-4-FlashNo verified data
GLM-5.1No verified data
GLM-5.2No verified data

Tool reliability, long-context recall and same-harness SWE-bench: untested, not zero.

CursorBench · 2026-09-22 ↗
Patch review example: why does an empty array slip through?

Editorial example, not measured model output. Review boundary contracts and regression tests; this is not a model ranking.

export function mean(values: number[]) {
  return values.reduce((a, b) => a + b, 0)
    / values.length;
}

// mean([]) => NaN
// Missing an explicit empty-input contract
⚙️ Select ModelGLM-4-Flash vs GLM-5.1 vs GLM-5.2
Slot 1Zhipu AI
Slot 2Zhipu AI
Slot 3Zhipu AI
GLM-4-Flash VS GLM-5.1 VS GLM-5.2
💳 View Plans↗

💰 Monthly Cost Simulation

Simulate monthly cost differences based on your estimated token usage volume

Monthly Input Tokens (Prompt)10 M tokens
Monthly Output Tokens (Completion)2 M tokens
GLM-4-Flash
$0.00/ mo
(in: $0 + out: $0)
GLM-5.1
$22.80/ mo
(in: $1.4 + out: $4.4)
GLM-5.2
$22.80/ mo
(in: $1.4 + out: $4.4)
AttributeGLM-4-FlashZhipu AIGLM-5.1Zhipu AIGLM-5.2Zhipu AI
Input$0$1.40$1.40
Output$0$4.40$4.40
Context128K128K256K
CursorBench Pass Rate———
StatusVerifiedVerifiedVerified
Tags & CapabilitiesFree tier, FastFlagship, Coding, ReasoningFlagship, Coding, Reasoning
LMArena Code#—#39#19
LMArena Agent#—#—#18
CursorBench#—#—#—
Artificial Analysis#—#46#36
Vals AI#—#—#—
LiveBench#—#—#33
LMArena Text#—#32#21
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