Model comparison
Claude 3.5 Haiku vs DeepSeek-V3
DeepSeek-V3 is the stronger model overall, scoring 39.5 to 29.2 on the Noometry Index.
Last verified . 45 shared benchmarks.
Summary
- They share 45 benchmarks with published results for both. Claude 3.5 Haiku scores higher in 1 category and DeepSeek-V3 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3 leads 37.5 to 18.7.
- The biggest single-benchmark swing is LiveBench Math: 35.5% for Claude 3.5 Haiku and 73.5% for DeepSeek-V3.
- DeepSeek-V3 has downloadable open weights; the other is API-only.
Side by side
| Claude 3.5 Haiku | DeepSeek-V3 | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 29.2 | 39.5 |
| Released | 2024-10-22 | 2024-12-26 |
| Weights | Proprietary | Open |
| Context window | — | 164K |
| Max output | — | 164K |
| Input $ / M tokens | — | $0.24 |
| Output $ / M tokens | — | $0.90 |
| Results tracked | 49 | 60 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding DeepSeek-V3 leads
Claude 3.5 Haiku: 32.9 (#265), DeepSeek-V3: 42.3 (#106)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| Aider Polyglot | 28% | 55.1% |
| SciCode | 27.4% | 35.8% |
| WeirdML | 30.7% | 36.1% |
| BigCodeBench Instruct | 46.1% | 50% |
| LiveBench Coding | 51.4% | 70.9% |
| LMArena Coding | 1286 | 1368 |
| BigCodeBench Complete | 59% | 62.2% |
| CadEval | 32% | — |
| HumanEval+ | — | 86.6% |
| MBPP+ | — | 73% |
Agentic & Tool Use Not comparable
Claude 3.5 Haiku: 28.0 (#95), DeepSeek-V3: —
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| BALROG | 19.3% | — |
| METR Time Horizons | — | 49.6% |
Reasoning DeepSeek-V3 leads
Claude 3.5 Haiku: 17.7 (#290), DeepSeek-V3: 20.5 (#236)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| CritPt | 0% | 0% |
| LiveBench Reasoning | 28.1% | 65.8% |
| LMArena Hard Prompts | 1251 | 1365 |
| DTBench | 56.7% | 64.8% |
| LiveBench Data Analysis | 48.5% | 60.9% |
| Epoch Capabilities Index | 127.15 | 135.94 |
| LiveBench | 43.5% | 66.9% |
| SimpleBench | — | 27.2% |
| Kagi LLM Benchmark | — | 52.3% |
| LMCA | — | 15.5% |
| BIG-Bench Hard | — | 87.5% |
| ForecastBench | — | 59.1 |
| HellaSwag | — | 88.9% |
| PIQA | — | 84.7% |
| WinoGrande | — | 85.2% |
Math DeepSeek-V3 leads
Claude 3.5 Haiku: 14.7 (#300), DeepSeek-V3: 32.1 (#219)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 4.3% | 37.8% |
| Omni-MATH | 22.4% | 40.3% |
| LiveBench Math | 35.5% | 73.5% |
| LMArena Math | 1244 | 1373 |
| MATH Level 5 | 46.4% | 75.5% |
| FrontierMath (Feb 2025 set) | 0.3% | 1.7% |
Knowledge DeepSeek-V3 leads
Claude 3.5 Haiku: 18.7 (#281), DeepSeek-V3: 37.5 (#155)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| GPQA Diamond | 38.1% | 67.6% |
| MMLU-Pro | 60.5% | 72.3% |
| Confabulations | 36.7% | 26.1% |
| GPQA (HELM) | 36.3% | 53.8% |
| LMArena Expert | 1208 | 1351 |
| MMLU | 74.3% | 87.2% |
| Vectara Hallucination Rate | — | 6.1% |
| ARC (AI2) Challenge | — | 95.3% |
| TriviaQA | — | 82.9% |
Multimodal Not comparable
Claude 3.5 Haiku: 26.8 (#117), DeepSeek-V3: —
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| LMArena Vision | 1092 | — |
| GeoBench | 34% | — |
Multilingual DeepSeek-V3 leads
Claude 3.5 Haiku: 40.0 (#218), DeepSeek-V3: 48.5 (#143)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| LMArena Non-English | 1238 | 1358 |
| LMArena Chinese | 1229 | 1391 |
| LMArena French | 1264 | 1385 |
| LMArena German | 1237 | 1374 |
| LMArena Japanese | 1175 | 1333 |
| LMArena Korean | 1173 | 1319 |
| LMArena Russian | 1253 | 1373 |
| LMArena Spanish | 1261 | 1358 |
Instruction Following DeepSeek-V3 leads
Claude 3.5 Haiku: 62.9 (#234), DeepSeek-V3: 72.8 (#130)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| LiveBench Instruction Following | 61.9% | 81.5% |
| IFEval | 79.2% | 83.2% |
| LMArena Instruction Following | 1241 | 1345 |
Long Context Claude 3.5 Haiku leads
Claude 3.5 Haiku: 38.3 (#200), DeepSeek-V3: 34.0 (#253)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| LMArena Longer Query | 1261 | 1352 |
| Fiction.LiveBench | — | 50% |
Writing & Preference DeepSeek-V3 leads
Claude 3.5 Haiku: 42.7 (#234), DeepSeek-V3: 57.4 (#130)
| Benchmark | Claude 3.5 Haiku | DeepSeek-V3 |
|---|---|---|
| LMArena Text | 1255 | 1375 |
| LMArena Creative Writing | 1233 | 1364 |
| Short-Story Creative Writing | 73.5% | 77% |
| EQ-Bench Creative Writing | 1146 | 1472 |
| WildBench | 76% | 83% |
| LMArena Multi-Turn | 1265 | 1389 |
| LiveBench Language | 35.4% | 49.1% |
Frequently asked questions
Is Claude 3.5 Haiku better than DeepSeek-V3?
DeepSeek-V3 is the stronger model overall, scoring 39.5 to 29.2 on the Noometry Index.
Is Claude 3.5 Haiku or DeepSeek-V3 better for coding?
DeepSeek-V3 scores higher on coding benchmarks: 42.3 versus 32.9 in the Noometry coding category.
How many benchmarks do Claude 3.5 Haiku and DeepSeek-V3 share?
45 benchmarks have published results for both models. Claude 3.5 Haiku has 49 scored results on Noometry and DeepSeek-V3 has 60.