Model comparison
Deepseek Coder v2 vs GLM-4.5
GLM-4.5 is the stronger model overall, scoring 42.0 to 35.9 on the Noometry Index.
Last verified . 17 shared benchmarks.
DeepSeekSummary
- They share 17 benchmarks with published results for both. Deepseek Coder v2 scores higher in 0 categories and GLM-4.5 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5 leads 57.5 to 38.2.
Side by side
| Deepseek Coder v2 | GLM-4.5 | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 35.9 | 42.0 |
| Released | 2024-06-17 | 2025-07-27 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 98K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $2.20 |
| Results tracked | 24 | 27 |
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Category by category
Coding GLM-4.5 leads
Deepseek Coder v2: 38.1 (#183), GLM-4.5: 41.4 (#125)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Coding | 1251 | 1434 |
| SWE-bench Verified (bash only) | — | 54.2% |
| WeirdML | — | 40.6% |
| BigCodeBench Instruct | 48.2% | — |
| BigCodeBench Complete | 59.7% | — |
| ALE-Bench | — | 344.82 |
| AlgoTune | — | 1.52 |
| HumanEval+ | 82.3% | — |
| MBPP+ | 75.1% | — |
Reasoning GLM-4.5 leads
Deepseek Coder v2: 23.6 (#176), GLM-4.5: 28.6 (#100)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Hard Prompts | 1207 | 1429 |
| Kagi LLM Benchmark | — | 57.9% |
| WinoGrande | 83.7% | — |
Math GLM-4.5 leads
Deepseek Coder v2: 34.9 (#190), GLM-4.5: 39.0 (#116)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Math | 1241 | 1427 |
| GSM8K | 94.5% | — |
Knowledge GLM-4.5 leads
Deepseek Coder v2: 32.3 (#212), GLM-4.5: 35.9 (#179)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Expert | 1181 | 1433 |
| Humanity's Last Exam | — | 8.3% |
| Confabulations | — | 11.3% |
| ARC (AI2) Challenge | 64.3% | — |
Multilingual GLM-4.5 leads
Deepseek Coder v2: 36.3 (#240), GLM-4.5: 52.8 (#77)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Non-English | 1182 | 1417 |
| LMArena Chinese | 1201 | 1465 |
| LMArena French | 1185 | 1418 |
| LMArena German | 1164 | 1407 |
| LMArena Japanese | 1126 | 1415 |
| LMArena Korean | 1104 | 1380 |
| LMArena Russian | 1188 | 1414 |
| LMArena Spanish | 1153 | 1454 |
Instruction Following GLM-4.5 leads
Deepseek Coder v2: 61.7 (#242), GLM-4.5: 74.1 (#104)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Instruction Following | 1180 | 1404 |
Long Context GLM-4.5 leads
Deepseek Coder v2: 37.0 (#224), GLM-4.5: 38.2 (#201)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Longer Query | 1219 | 1412 |
| Fiction.LiveBench | — | 58.3% |
Writing & Preference GLM-4.5 leads
Deepseek Coder v2: 38.2 (#253), GLM-4.5: 57.5 (#127)
| Benchmark | Deepseek Coder v2 | GLM-4.5 |
|---|---|---|
| LMArena Text | 1191 | 1430 |
| LMArena Creative Writing | 1120 | 1395 |
| LMArena Multi-Turn | 1177 | 1415 |
| Short-Story Creative Writing | — | 73.4% |
| EQ-Bench Creative Writing | — | 1343 |
Frequently asked questions
Is Deepseek Coder v2 better than GLM-4.5?
GLM-4.5 is the stronger model overall, scoring 42.0 to 35.9 on the Noometry Index.
Is Deepseek Coder v2 or GLM-4.5 better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 38.1 in the Noometry coding category.
How many benchmarks do Deepseek Coder v2 and GLM-4.5 share?
17 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and GLM-4.5 has 27.