Model comparison
DeepSeek-V3.2-Speciale vs ERNIE 5.0 0110
ERNIE 5.0 0110 is the stronger model overall, scoring 41.2 to 39.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
BaiduSummary
- The widest gap is in writing & preference, where ERNIE 5.0 0110 leads 63.4 to 46.1.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 | |
|---|---|---|
| Provider | DeepSeek | Baidu |
| Noometry Index | 39.1 | 41.2 |
| Released | 2025-12-01 | — |
| Weights | Open | Proprietary |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 20 |
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Category by category
Coding ERNIE 5.0 0110 leads
DeepSeek-V3.2-Speciale: 39.9 (#136), ERNIE 5.0 0110: 42.3 (#94)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1455 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), ERNIE 5.0 0110: 16.3 (#296)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| SimpleBench | 52.6% | — |
| NYT Connections (extended) | — | 10.3% |
| Thematic Generalization | — | 41.7% |
| LMArena Hard Prompts | — | 1446 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, ERNIE 5.0 0110: 36.5 (#111)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Math | — | 1437 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, ERNIE 5.0 0110: 39.2 (#125)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Expert | — | 1427 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, ERNIE 5.0 0110: 39.1 (#49)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Vision | — | 1248 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, ERNIE 5.0 0110: 54.3 (#47)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Non-English | — | 1436 |
| LMArena Chinese | — | 1512 |
| LMArena French | — | 1466 |
| LMArena German | — | 1462 |
| LMArena Japanese | — | 1383 |
| LMArena Korean | — | 1406 |
| LMArena Russian | — | 1446 |
| LMArena Spanish | — | 1473 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, ERNIE 5.0 0110: 74.7 (#88)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Instruction Following | — | 1413 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, ERNIE 5.0 0110: 43.4 (#90)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Longer Query | — | 1422 |
Writing & Preference ERNIE 5.0 0110 leads
DeepSeek-V3.2-Speciale: 46.1 (#217), ERNIE 5.0 0110: 63.4 (#64)
| Benchmark | DeepSeek-V3.2-Speciale | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Text | — | 1445 |
| LMArena Creative Writing | — | 1426 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1433 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than ERNIE 5.0 0110?
ERNIE 5.0 0110 is the stronger model overall, scoring 41.2 to 39.1 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or ERNIE 5.0 0110 better for coding?
ERNIE 5.0 0110 scores higher on coding benchmarks: 42.3 versus 39.9 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and ERNIE 5.0 0110 share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and ERNIE 5.0 0110 has 20.