Comparing 2 models

Gemini 4 Argon vs GLM 5.2

Benchmarks through

Verdict

Gemini 4 Argon and GLM 5.2 are not yet ranked on the same task, so compare the specifications below. GLM 5.2 costs 58.7x less per input token. Only GLM 5.2 has open weights for self-hosting.

  • Choose GLM 5.2 for you need to self-host.

Built from the published task rankings below; ranks come from each task's own weighted benchmarks, so a win on one task says nothing about another.

metric
Model 1Gemini 4 Argon
Model 2GLM 5.2
Best for
a General Assistant (#1)
Best Cheap LLM for High Volume (#2)
Provider
google
z-ai
Context
1.0MBest
1.0MBest
Input / 1M
$2
$0.034Best
Output / 1M
$10
$7Best
Tool use
yesBest
yesBest
Vision
yesBest
—
Reasoning
yesBest
yesBest
Open-weight
—
yesBest
Released
Oct 13, 2026
Jun 13, 2026

Measured head to head

Benchmarks both models were run on

EvaluationGemini 4 ArgonGLM 5.2Source
Design Arena Coding1329 Elo1287 Elosource · 2026-10-23
Design Arena UI1333 Elo1294 Elosource · 2026-10-23
Design Arena Website1316 Elo1285 Elosource · 2026-10-23
FrontierMath Tiers 1-3 (Epoch AI)86% ± 2.159.2% ± 3source · 2026-10-13
GPQA Diamond (Epoch AI)96.4% ± 1.291.9% ± 1.6source · 2026-10-13
LMArena Agent122.1source · 2026-10-20
LMArena Agent Bash Recovery-21.40.7source · 2026-10-08
LMArena Agent Steerability14.61.3source · 2026-10-20
LMArena Agent Task Outcome13.83.8source · 2026-10-20
LMArena Agent Tool Hallucination0.30.7source · 2026-10-20
LMArena Creative Writing1523 Elo1462 Elosource · 2026-10-22
LMArena Instruction Following1528 Elo1466 Elosource · 2026-10-22
LMArena Long Query1538 Elo1479 Elosource · 2026-10-22
LMArena Math1538 Elo1484 Elosource · 2026-10-22
LMArena Text1517 Elo1475 Elosource · 2026-10-22
LMArena Text Factuality1498 Elo1463 Elosource · 2026-10-22
LMArena WebDev1673 Elo1604 Elosource · 2026-10-22
OTIS Mock AIME (Epoch AI)100% ± 086.4% ± 4.2source · 2026-10-13
SimpleQA Verified (Epoch AI)76% ± 1.434.2% ± 1.5source · 2026-10-13

Values are as published by each evaluator, in its own units; rows from different evaluators are not on a common scale.