Model comparison
DeepSeek-V3 vs ERNIE 5.1
ERNIE 5.1 is the stronger model overall, scoring 43.8 to 39.5 on the Noometry Index.
Last verified . 17 shared benchmarks.
DeepSeek
BaiduSummary
- They share 17 benchmarks with published results for both. DeepSeek-V3 scores higher in 0 categories and ERNIE 5.1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where ERNIE 5.1 leads 44.7 to 34.0.
- DeepSeek-V3 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3 | ERNIE 5.1 | |
|---|---|---|
| Provider | DeepSeek | Baidu |
| Noometry Index | 39.5 | 43.8 |
| Released | 2024-12-26 | — |
| Weights | Open | Proprietary |
| Context window | 164K | — |
| Max output | 164K | — |
| Input $ / M tokens | $0.24 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 60 | 19 |
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Category by category
Coding ERNIE 5.1 leads
DeepSeek-V3: 42.3 (#106), ERNIE 5.1: 44.0 (#76)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Coding | 1368 | 1488 |
| Aider Polyglot | 55.1% | — |
| SciCode | 35.8% | — |
| WeirdML | 36.1% | — |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| BigCodeBench Complete | 62.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |
Agentic & Tool Use Not comparable
DeepSeek-V3: —, ERNIE 5.1: —
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Search | — | 1227 |
| METR Time Horizons | 49.6% | — |
Reasoning ERNIE 5.1 leads
DeepSeek-V3: 20.5 (#236), ERNIE 5.1: 21.9 (#211)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Hard Prompts | 1365 | 1481 |
| SimpleBench | 27.2% | — |
| Kagi LLM Benchmark | 52.3% | — |
| NYT Connections (extended) | — | 23.4% |
| CritPt | 0% | — |
| LiveBench Reasoning | 65.8% | — |
| DTBench | 64.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 15.5% | — |
| BIG-Bench Hard | 87.5% | — |
| Epoch Capabilities Index | 135.94 | — |
| ForecastBench | 59.1 | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |
Math ERNIE 5.1 leads
DeepSeek-V3: 32.1 (#219), ERNIE 5.1: 40.3 (#92)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Math | 1373 | 1481 |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| Omni-MATH | 40.3% | — |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |
Knowledge ERNIE 5.1 leads
DeepSeek-V3: 37.5 (#155), ERNIE 5.1: 41.9 (#102)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Expert | 1351 | 1492 |
| GPQA Diamond | 67.6% | — |
| MMLU-Pro | 72.3% | — |
| Confabulations | 26.1% | — |
| Vectara Hallucination Rate | 6.1% | — |
| GPQA (HELM) | 53.8% | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |
Multilingual ERNIE 5.1 leads
DeepSeek-V3: 48.5 (#143), ERNIE 5.1: 55.5 (#29)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Non-English | 1358 | 1454 |
| LMArena Chinese | 1391 | 1508 |
| LMArena French | 1385 | 1488 |
| LMArena German | 1374 | 1470 |
| LMArena Japanese | 1333 | 1422 |
| LMArena Korean | 1319 | 1427 |
| LMArena Russian | 1373 | 1459 |
| LMArena Spanish | 1358 | 1473 |
Instruction Following ERNIE 5.1 leads
DeepSeek-V3: 72.8 (#130), ERNIE 5.1: 76.7 (#37)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Instruction Following | 1345 | 1460 |
| LiveBench Instruction Following | 81.5% | — |
| IFEval | 83.2% | — |
Long Context ERNIE 5.1 leads
DeepSeek-V3: 34.0 (#253), ERNIE 5.1: 44.7 (#59)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Longer Query | 1352 | 1462 |
| Fiction.LiveBench | 50% | — |
Writing & Preference ERNIE 5.1 leads
DeepSeek-V3: 57.4 (#130), ERNIE 5.1: 65.1 (#52)
| Benchmark | DeepSeek-V3 | ERNIE 5.1 |
|---|---|---|
| LMArena Text | 1375 | 1468 |
| LMArena Creative Writing | 1364 | 1441 |
| LMArena Multi-Turn | 1389 | 1471 |
| Short-Story Creative Writing | 77% | — |
| EQ-Bench Creative Writing | 1472 | — |
| WildBench | 83% | — |
| LiveBench Language | 49.1% | — |
Frequently asked questions
Is DeepSeek-V3 better than ERNIE 5.1?
ERNIE 5.1 is the stronger model overall, scoring 43.8 to 39.5 on the Noometry Index.
Is DeepSeek-V3 or ERNIE 5.1 better for coding?
ERNIE 5.1 scores higher on coding benchmarks: 44.0 versus 42.3 in the Noometry coding category.
How many benchmarks do DeepSeek-V3 and ERNIE 5.1 share?
17 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and ERNIE 5.1 has 19.