Model comparison
ERNIE 5.0 0110 vs GLM-4.7
ERNIE 5.0 0110 and GLM-4.7 score almost the same on the Noometry Index (41.8 vs 42.0), so choose on price, context window or the category you care about most.
Last verified . 17 shared benchmarks.
BaiduSummary
- They share 17 benchmarks with published results for both. ERNIE 5.0 0110 scores higher in 5 categories and GLM-4.7 in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.7 leads 24.3 to 17.0.
- GLM-4.7 has downloadable open weights; the other is API-only.
Side by side
| ERNIE 5.0 0110 | GLM-4.7 | |
|---|---|---|
| Provider | Baidu | Z.ai (Zhipu) |
| Noometry Index | 41.8 | 42.0 |
| Released | — | 2025-12-22 |
| Weights | Proprietary | Open |
| Context window | — | 205K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $2.20 |
| Results tracked | 20 | 36 |
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Category by category
Coding Too close to call
ERNIE 5.0 0110: 43.0 (#94), GLM-4.7: 44.0 (#79)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Coding | 1455 | 1454 |
| LMArena WebDev | — | 1435 |
| SciCode | — | 45.1% |
| ALE-Bench | — | 399.48 |
Agentic & Tool Use Not comparable
ERNIE 5.0 0110: —, GLM-4.7: 26.5 (#103)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| Terminal-Bench | — | 33.4% |
| Vending-Bench 2 | — | 2,377 |
Reasoning GLM-4.7 leads
ERNIE 5.0 0110: 17.0 (#297), GLM-4.7: 24.3 (#164)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Hard Prompts | 1445 | 1443 |
| SimpleBench | — | 47.7% |
| NYT Connections (extended) | 10.3% | — |
| CritPt | — | 1.7% |
| Chess Puzzles | — | 6% |
| Thematic Generalization | 41.7% | — |
| Epoch Capabilities Index | — | 143.51 |
Math Too close to call
ERNIE 5.0 0110: 39.3 (#110), GLM-4.7: 38.6 (#135)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Math | 1437 | 1423 |
| OTIS Mock AIME 2024-2025 | — | 83.3% |
| ProofBench | — | 6% |
| FrontierMath (Feb 2025 set) | — | 2.4% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GLM-4.7 leads
ERNIE 5.0 0110: 39.8 (#128), GLM-4.7: 47.0 (#80)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Expert | 1428 | 1424 |
| GPQA Diamond | — | 83.3% |
| SimpleQA Verified | — | 32.2% |
| Vectara Hallucination Rate | — | 11.7% |
Multimodal Not comparable
ERNIE 5.0 0110: 39.9 (#53), GLM-4.7: —
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Vision | 1249 | — |
Multilingual ERNIE 5.0 0110 leads
ERNIE 5.0 0110: 54.1 (#49), GLM-4.7: 52.8 (#79)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Non-English | 1436 | 1417 |
| LMArena Chinese | 1512 | 1495 |
| LMArena French | 1467 | 1432 |
| LMArena German | 1460 | 1424 |
| LMArena Japanese | 1382 | 1439 |
| LMArena Korean | 1406 | 1399 |
| LMArena Russian | 1446 | 1423 |
| LMArena Spanish | 1473 | 1434 |
Instruction Following Too close to call
ERNIE 5.0 0110: 74.5 (#92), GLM-4.7: 74.4 (#95)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Instruction Following | 1413 | 1411 |
Long Context Too close to call
ERNIE 5.0 0110: 43.4 (#95), GLM-4.7: 42.8 (#116)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Longer Query | 1422 | 1432 |
| CL-bench | — | 15.9% |
| CL-bench Life | — | 10.9% |
Writing & Preference ERNIE 5.0 0110 leads
ERNIE 5.0 0110: 63.1 (#66), GLM-4.7: 60.9 (#93)
| Benchmark | ERNIE 5.0 0110 | GLM-4.7 |
|---|---|---|
| LMArena Text | 1445 | 1435 |
| LMArena Creative Writing | 1426 | 1401 |
| LMArena Multi-Turn | 1434 | 1446 |
| EQ-Bench Creative Writing | — | 1413 |
Frequently asked questions
Is ERNIE 5.0 0110 better than GLM-4.7?
ERNIE 5.0 0110 and GLM-4.7 score almost the same on the Noometry Index (41.8 vs 42.0), so choose on price, context window or the category you care about most.
Is ERNIE 5.0 0110 or GLM-4.7 better for coding?
They score almost the same on coding (43.0 vs 44.0); test both on your own repository before choosing.
How many benchmarks do ERNIE 5.0 0110 and GLM-4.7 share?
17 benchmarks have published results for both models. ERNIE 5.0 0110 has 20 scored results on Noometry and GLM-4.7 has 36.