Noometry

Model comparison

DeepSeek LLM 67B vs GLM-5.3-Flash

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 24.9 on the Noometry Index.

Last verified . 14 shared benchmarks.

DeepSeek LLM 67B DeepSeek

24.9

Rank #347 Confirmed

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Summary

  • They share 14 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and GLM-5.3-Flash in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 7.0.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.8% for DeepSeek LLM 67B and 93.9% for GLM-5.3-Flash.

Side by side

DeepSeek LLM 67BGLM-5.3-Flash
ProviderDeepSeekZ.ai (Zhipu)
Noometry Index24.951.8
Released2023-11-292026-08-20
WeightsOpenOpen
Context window—1M
Max output—131K
Input $ / M tokens—$0.15
Output $ / M tokens—$0.50
Results tracked1540

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Category by category

Coding GLM-5.3-Flash leads

DeepSeek LLM 67B: 31.9 (#278), GLM-5.3-Flash: 53.1 (#31)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
LMArena Coding10961508
DeepSWE—63.4%
FrontierCode—31.8%
CursorBench—36.8%
LMArena WebDev—1609
FrontierSWE—18.1%
SciCode—51.6%
ALE-Bench—303.55

Agentic & Tool Use Not comparable

DeepSeek LLM 67B: —, GLM-5.3-Flash: 34.2 (#47)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
APEX-Agents—52.8%
GDP.pdf—14%

Reasoning GLM-5.3-Flash leads

DeepSeek LLM 67B: 16.5 (#304), GLM-5.3-Flash: 48.0 (#42)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
Chess Puzzles0%14%
LMArena Hard Prompts10701491
Epoch Capabilities Index110.5151.88
ARC-AGI-2—65.8%
ARC-AGI-1—91%
CritPt—15.4%
Mystery Game Puzzles—8%
Surface Evolver Bench—52.5%
Bench to the Future 3—0.15

Math GLM-5.3-Flash leads

DeepSeek LLM 67B: 8.7 (#324), GLM-5.3-Flash: 53.3 (#47)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
OTIS Mock AIME 2024-20250.8%93.9%
LMArena Math11081500
FrontierMath (Tiers 1-3)—55.8%
FrontierMath Tier 4—17.1%
ProofBench—21%
MATH Level 56.4%—

Knowledge GLM-5.3-Flash leads

DeepSeek LLM 67B: 7.0 (#313), GLM-5.3-Flash: 58.4 (#36)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
GPQA Diamond24.6%90.2%
LMArena Expert—1513

Multimodal Not comparable

DeepSeek LLM 67B: —, GLM-5.3-Flash: 42.8 (#27)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
LMArena Vision—1296

Multilingual GLM-5.3-Flash leads

DeepSeek LLM 67B: 29.4 (#267), GLM-5.3-Flash: 56.0 (#25)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
LMArena Non-English10731462
LMArena Chinese11321527
LMArena French—1496
LMArena German—1470
LMArena Japanese—1429
LMArena Korean—1446
LMArena Russian—1469
LMArena Spanish—1471

Instruction Following GLM-5.3-Flash leads

DeepSeek LLM 67B: 55.4 (#277), GLM-5.3-Flash: 77.5 (#20)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
LMArena Instruction Following10791478

Long Context GLM-5.3-Flash leads

DeepSeek LLM 67B: 33.1 (#265), GLM-5.3-Flash: 45.4 (#39)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
LMArena Longer Query10921482

Writing & Preference GLM-5.3-Flash leads

DeepSeek LLM 67B: 31.6 (#282), GLM-5.3-Flash: 65.3 (#50)

BenchmarkDeepSeek LLM 67BGLM-5.3-Flash
LMArena Text11051471
LMArena Creative Writing10671442
LMArena Multi-Turn10821467

Frequently asked questions

Is DeepSeek LLM 67B better than GLM-5.3-Flash?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 24.9 on the Noometry Index.

Is DeepSeek LLM 67B or GLM-5.3-Flash better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 31.9 in the Noometry coding category.

How many benchmarks do DeepSeek LLM 67B and GLM-5.3-Flash share?

14 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and GLM-5.3-Flash has 40.

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