Model comparison
Deepseek Coder v2 vs GLM-4.7-Flash
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 35.9 on the Noometry Index.
Last verified . 16 shared benchmarks.
DeepSeekSummary
- They share 16 benchmarks with published results for both. Deepseek Coder v2 scores higher in 1 category and GLM-4.7-Flash in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.7-Flash leads 46.5 to 36.3.
Side by side
| Deepseek Coder v2 | GLM-4.7-Flash | |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 35.9 | 38.8 |
| Released | 2024-06-17 | 2026-01-19 |
| Weights | Open | Open |
| Context window | — | 200K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.06 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 24 | 21 |
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Category by category
Coding GLM-4.7-Flash leads
Deepseek Coder v2: 38.1 (#183), GLM-4.7-Flash: 40.6 (#135)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1251 | 1383 |
| BigCodeBench Instruct | 48.2% | — |
| BigCodeBench Complete | 59.7% | — |
| HumanEval+ | 82.3% | — |
| MBPP+ | 75.1% | — |
Reasoning Deepseek Coder v2 leads
Deepseek Coder v2: 23.6 (#176), GLM-4.7-Flash: 20.9 (#229)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Hard Prompts | 1207 | 1356 |
| Chess Puzzles | — | 0% |
| WinoGrande | 83.7% | — |
Math GLM-4.7-Flash leads
Deepseek Coder v2: 34.9 (#190), GLM-4.7-Flash: 36.1 (#173)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Math | 1241 | 1355 |
| OTIS Mock AIME 2024-2025 | — | 58.3% |
| GSM8K | 94.5% | — |
Knowledge GLM-4.7-Flash leads
Deepseek Coder v2: 32.3 (#212), GLM-4.7-Flash: 35.5 (#184)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Expert | 1181 | 1357 |
| GPQA Diamond | — | 60.5% |
| Vectara Hallucination Rate | — | 9.3% |
| ARC (AI2) Challenge | 64.3% | — |
Multilingual GLM-4.7-Flash leads
Deepseek Coder v2: 36.3 (#240), GLM-4.7-Flash: 46.5 (#158)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1182 | 1330 |
| LMArena Chinese | 1201 | 1403 |
| LMArena French | 1185 | 1332 |
| LMArena German | 1164 | 1337 |
| LMArena Korean | 1104 | 1283 |
| LMArena Russian | 1188 | 1332 |
| LMArena Spanish | 1153 | 1350 |
| LMArena Japanese | 1126 | — |
Instruction Following GLM-4.7-Flash leads
Deepseek Coder v2: 61.7 (#242), GLM-4.7-Flash: 70.1 (#167)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1180 | 1327 |
Long Context GLM-4.7-Flash leads
Deepseek Coder v2: 37.0 (#224), GLM-4.7-Flash: 40.9 (#148)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1219 | 1345 |
Writing & Preference GLM-4.7-Flash leads
Deepseek Coder v2: 38.2 (#253), GLM-4.7-Flash: 47.4 (#210)
| Benchmark | Deepseek Coder v2 | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1191 | 1351 |
| LMArena Creative Writing | 1120 | 1297 |
| LMArena Multi-Turn | 1177 | 1342 |
| EQ-Bench Creative Writing | — | 1125 |
Frequently asked questions
Is Deepseek Coder v2 better than GLM-4.7-Flash?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 35.9 on the Noometry Index.
Is Deepseek Coder v2 or GLM-4.7-Flash better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 38.1 in the Noometry coding category.
How many benchmarks do Deepseek Coder v2 and GLM-4.7-Flash share?
16 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and GLM-4.7-Flash has 21.