Model comparison
DeepSeek LLM 67B vs GLM-5.3
GLM-5.3 is the stronger model overall, scoring 54.6 to 24.8 on the Noometry Index.
Last verified . 14 shared benchmarks.
Summary
- They share 14 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and GLM-5.3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.1 to 8.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.8% for DeepSeek LLM 67B and 91.1% for GLM-5.3.
Side by side
| DeepSeek LLM 67B | GLM-5.3 | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 24.8 | 54.6 |
| Released | 2023-11-29 | 2026-08-14 |
| Weights | Open | Open |
| Context window | — | 1M |
| Max output | — | 131K |
| Input $ / M tokens | — | $1.40 |
| Output $ / M tokens | — | $4.40 |
| Results tracked | 15 | 41 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-5.3 leads
DeepSeek LLM 67B: 31.3 (#273), GLM-5.3: 59.0 (#12)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Coding | 1096 | 1499 |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| LMArena WebDev | — | 1623 |
| FrontierSWE | — | 30.2% |
| SciCode | — | 59% |
| WeirdML | — | 75.4% |
| ALE-Bench | — | 1,317 |
Agentic & Tool Use Not comparable
DeepSeek LLM 67B: —, GLM-5.3: 36.3 (#34)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| APEX-Agents | — | 56.6% |
| Vending-Bench 2 | — | 8,164 |
Reasoning GLM-5.3 leads
DeepSeek LLM 67B: 15.9 (#300), GLM-5.3: 45.2 (#42)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| Chess Puzzles | 0% | 21% |
| LMArena Hard Prompts | 1070 | 1491 |
| Epoch Capabilities Index | 110.54 | 155.56 |
| NYT Connections (extended) | — | 74.2% |
| CritPt | — | 19.1% |
| Mystery Game Puzzles | — | 33% |
| DTBench | — | 87.7% |
| LMCA | — | 55.5% |
| Bench to the Future 3 | — | 0.15 |
Math GLM-5.3 leads
DeepSeek LLM 67B: 8.1 (#318), GLM-5.3: 62.1 (#27)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 91.1% |
| LMArena Math | 1108 | 1493 |
| FrontierMath (Tiers 1-3) | — | 68.8% |
| FrontierMath Tier 4 | — | 29.3% |
| ProofBench | — | 49% |
| MATH Level 5 | 6.4% | — |
Knowledge GLM-5.3 leads
DeepSeek LLM 67B: 7.1 (#308), GLM-5.3: 58.3 (#34)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| GPQA Diamond | 24.6% | 90.9% |
| SimpleQA Verified | — | 41% |
| LMArena Expert | — | 1512 |
Multilingual GLM-5.3 leads
DeepSeek LLM 67B: 29.5 (#262), GLM-5.3: 55.9 (#27)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1073 | 1457 |
| LMArena Chinese | 1132 | 1523 |
| LMArena French | — | 1499 |
| LMArena German | — | 1505 |
| LMArena Japanese | — | 1438 |
| LMArena Korean | — | 1478 |
| LMArena Russian | — | 1460 |
| LMArena Spanish | — | 1444 |
Instruction Following GLM-5.3 leads
DeepSeek LLM 67B: 55.7 (#272), GLM-5.3: 77.8 (#15)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1079 | 1481 |
Long Context GLM-5.3 leads
DeepSeek LLM 67B: 33.1 (#260), GLM-5.3: 45.5 (#32)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1092 | 1485 |
Writing & Preference GLM-5.3 leads
DeepSeek LLM 67B: 31.8 (#277), GLM-5.3: 75.9 (#6)
| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Text | 1105 | 1473 |
| LMArena Creative Writing | 1067 | 1459 |
| LMArena Multi-Turn | 1082 | 1473 |
| EQ-Bench Creative Writing | — | 2075 |
Frequently asked questions
Is DeepSeek LLM 67B better than GLM-5.3?
GLM-5.3 is the stronger model overall, scoring 54.6 to 24.8 on the Noometry Index.
Is DeepSeek LLM 67B or GLM-5.3 better for coding?
GLM-5.3 scores higher on coding benchmarks: 59.0 versus 31.3 in the Noometry coding category.
How many benchmarks do DeepSeek LLM 67B and GLM-5.3 share?
14 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and GLM-5.3 has 41.