Model comparison
DeepSeek V4 Pro vs ERNIE 5.0 0110
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 41.8 on the Noometry Index.
Last verified . 18 shared benchmarks.
DeepSeek
BaiduSummary
- They share 18 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 8 categories and ERNIE 5.0 0110 in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.5 to 17.0.
- The biggest single-benchmark swing is NYT Connections (extended): 91.3% for DeepSeek V4 Pro and 10.3% for ERNIE 5.0 0110.
- DeepSeek V4 Pro has downloadable open weights; the other is API-only.
Side by side
| DeepSeek V4 Pro | ERNIE 5.0 0110 | |
|---|---|---|
| Provider | DeepSeek | Baidu |
| Noometry Index | 54.3 | 41.8 |
| Released | 2026-04-24 | — |
| Weights | Open | Proprietary |
| Context window | 1M | — |
| Max output | 393K | — |
| Input $ / M tokens | $0.66 | — |
| Output $ / M tokens | $1.98 | — |
| Results tracked | 48 | 20 |
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Category by category
Coding DeepSeek V4 Pro leads
DeepSeek V4 Pro: 52.4 (#34), ERNIE 5.0 0110: 43.0 (#94)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Coding | 1470 | 1455 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| WeirdML | 66.2% | — |
| ALE-Bench | 1,403 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Pro: 32.8 (#58), ERNIE 5.0 0110: —
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |
Reasoning DeepSeek V4 Pro leads
DeepSeek V4 Pro: 56.5 (#24), ERNIE 5.0 0110: 17.0 (#297)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| NYT Connections (extended) | 91.3% | 10.3% |
| LMArena Hard Prompts | 1461 | 1445 |
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| Thematic Generalization | — | 41.7% |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.31 | — |
| ForecastBench | 56.1 | — |
Math DeepSeek V4 Pro leads
DeepSeek V4 Pro: 64.8 (#30), ERNIE 5.0 0110: 39.3 (#110)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Math | 1455 | 1437 |
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
Knowledge DeepSeek V4 Pro leads
DeepSeek V4 Pro: 59.5 (#31), ERNIE 5.0 0110: 39.8 (#128)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Expert | 1464 | 1428 |
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
| Vectara Hallucination Rate | 8.6% | — |
Multimodal Not comparable
DeepSeek V4 Pro: —, ERNIE 5.0 0110: 39.9 (#53)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Vision | — | 1249 |
Multilingual Too close to call
DeepSeek V4 Pro: 54.4 (#45), ERNIE 5.0 0110: 54.1 (#49)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Non-English | 1439 | 1436 |
| LMArena Chinese | 1486 | 1512 |
| LMArena French | 1472 | 1467 |
| LMArena German | 1458 | 1460 |
| LMArena Japanese | 1445 | 1382 |
| LMArena Korean | 1447 | 1406 |
| LMArena Russian | 1453 | 1446 |
| LMArena Spanish | 1458 | 1473 |
Instruction Following DeepSeek V4 Pro leads
DeepSeek V4 Pro: 76.1 (#47), ERNIE 5.0 0110: 74.5 (#92)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Instruction Following | 1448 | 1413 |
Long Context DeepSeek V4 Pro leads
DeepSeek V4 Pro: 45.0 (#51), ERNIE 5.0 0110: 43.4 (#95)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Longer Query | 1458 | 1422 |
| CL-bench Life | 13.5% | — |
Writing & Preference DeepSeek V4 Pro leads
DeepSeek V4 Pro: 65.5 (#46), ERNIE 5.0 0110: 63.1 (#66)
| Benchmark | DeepSeek V4 Pro | ERNIE 5.0 0110 |
|---|---|---|
| LMArena Text | 1451 | 1445 |
| LMArena Creative Writing | 1446 | 1426 |
| LMArena Multi-Turn | 1467 | 1434 |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |
Frequently asked questions
Is DeepSeek V4 Pro better than ERNIE 5.0 0110?
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 41.8 on the Noometry Index.
Is DeepSeek V4 Pro or ERNIE 5.0 0110 better for coding?
DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 43.0 in the Noometry coding category.
How many benchmarks do DeepSeek V4 Pro and ERNIE 5.0 0110 share?
18 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and ERNIE 5.0 0110 has 20.