Model comparison
DeepSeek LLM 67B vs GLM-4.5-Air
GLM-4.5-Air is the stronger model overall, scoring 38.7 to 24.8 on the Noometry Index.
Last verified . 10 shared benchmarks.
DeepSeekSummary
- They share 10 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and GLM-4.5-Air in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.5-Air leads 34.6 to 7.1.
Side by side
| DeepSeek LLM 67B | GLM-4.5-Air | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 24.8 | 38.7 |
| Released | 2023-11-29 | 2025-07-20 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 98K |
| Input $ / M tokens | — | $0.20 |
| Output $ / M tokens | — | $1.10 |
| Results tracked | 15 | 27 |
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Category by category
Coding GLM-4.5-Air leads
DeepSeek LLM 67B: 31.3 (#273), GLM-4.5-Air: 34.5 (#225)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| LMArena Coding | 1096 | 1397 |
| GSO | — | 2.9% |
Reasoning GLM-4.5-Air leads
DeepSeek LLM 67B: 15.9 (#300), GLM-4.5-Air: 23.3 (#166)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| LMArena Hard Prompts | 1070 | 1379 |
| Kagi LLM Benchmark | — | 43% |
| Chess Puzzles | 0% | — |
| Epoch Capabilities Index | 110.54 | — |
| ForecastBench | — | 59.2 |
Math GLM-4.5-Air leads
DeepSeek LLM 67B: 8.1 (#318), GLM-4.5-Air: 33.8 (#166)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| LMArena Math | 1108 | 1396 |
| OTIS Mock AIME 2024-2025 | 0.8% | — |
| Omni-MATH | — | 39.1% |
| MATH Level 5 | 6.4% | — |
Knowledge GLM-4.5-Air leads
DeepSeek LLM 67B: 7.1 (#308), GLM-4.5-Air: 34.6 (#184)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| GPQA Diamond | 24.6% | — |
| Humanity's Last Exam | — | 8.1% |
| MMLU-Pro | — | 76.2% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 59.4% |
| LMArena Expert | — | 1370 |
Multilingual GLM-4.5-Air leads
DeepSeek LLM 67B: 29.5 (#262), GLM-4.5-Air: 49.4 (#130)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| LMArena Non-English | 1073 | 1366 |
| LMArena Chinese | 1132 | 1427 |
| LMArena French | — | 1399 |
| LMArena German | — | 1376 |
| LMArena Japanese | — | 1348 |
| LMArena Korean | — | 1306 |
| LMArena Russian | — | 1373 |
| LMArena Spanish | — | 1385 |
Instruction Following GLM-4.5-Air leads
DeepSeek LLM 67B: 55.7 (#272), GLM-4.5-Air: 69.8 (#165)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| LMArena Instruction Following | 1079 | 1353 |
| IFEval | — | 81.2% |
Long Context GLM-4.5-Air leads
DeepSeek LLM 67B: 33.1 (#260), GLM-4.5-Air: 41.6 (#130)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| LMArena Longer Query | 1092 | 1367 |
Writing & Preference GLM-4.5-Air leads
DeepSeek LLM 67B: 31.8 (#277), GLM-4.5-Air: 56.1 (#134)
| Benchmark | DeepSeek LLM 67B | GLM-4.5-Air |
|---|---|---|
| LMArena Text | 1105 | 1384 |
| LMArena Creative Writing | 1067 | 1343 |
| LMArena Multi-Turn | 1082 | 1371 |
| WildBench | — | 78.9% |
Frequently asked questions
Is DeepSeek LLM 67B better than GLM-4.5-Air?
GLM-4.5-Air is the stronger model overall, scoring 38.7 to 24.8 on the Noometry Index.
Is DeepSeek LLM 67B or GLM-4.5-Air better for coding?
GLM-4.5-Air scores higher on coding benchmarks: 34.5 versus 31.3 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and GLM-4.5-Air share?
10 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and GLM-4.5-Air has 27.