Model comparison
Claude Haiku 4.5 vs Deepseek Coder v2
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 35.9 on the Noometry Index.
Last verified . 17 shared benchmarks.
DeepSeekSummary
- They share 17 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 7 categories and Deepseek Coder v2 in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Haiku 4.5 leads 57.9 to 38.2.
- Deepseek Coder v2 has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Deepseek Coder v2 | |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Noometry Index | 39.5 | 35.9 |
| Released | 2025-10-15 | 2024-06-17 |
| Weights | Proprietary | Open |
| Context window | 200K | — |
| Max output | 64K | — |
| Input $ / M tokens | $1 | — |
| Output $ / M tokens | $5 | — |
| Results tracked | 53 | 24 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.0 (#78), Deepseek Coder v2: 38.1 (#183)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Coding | 1453 | 1251 |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| SciCode | 43.3% | — |
| WeirdML | 45.4% | — |
| BigCodeBench Instruct | — | 48.2% |
| BigCodeBench Complete | — | 59.7% |
| ALE-Bench | 653.48 | — |
| HumanEval+ | — | 82.3% |
| MBPP+ | — | 75.1% |
Agentic & Tool Use Not comparable
Claude Haiku 4.5: 33.6 (#52), Deepseek Coder v2: —
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| Terminal-Bench | 35.5% | — |
| Berkeley Function Calling Leaderboard | 68.7% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |
Reasoning Deepseek Coder v2 leads
Claude Haiku 4.5: 15.1 (#320), Deepseek Coder v2: 23.6 (#176)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Hard Prompts | 1420 | 1207 |
| ARC-AGI-2 | 4% | — |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| CritPt | 0% | — |
| Chess Puzzles | 8% | — |
| DTBench | 73.6% | — |
| LMCA | 30.9% | — |
| Epoch Capabilities Index | 142.41 | — |
| ForecastBench | 61.4 | — |
| WinoGrande | — | 83.7% |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.9 (#78), Deepseek Coder v2: 34.9 (#190)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Math | 1396 | 1241 |
| OTIS Mock AIME 2024-2025 | 66.7% | — |
| Omni-MATH | 56.1% | — |
| MATH Level 5 | 96.4% | — |
| FrontierMath (Feb 2025 set) | 5.9% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
| GSM8K | — | 94.5% |
Knowledge Claude Haiku 4.5 leads
Claude Haiku 4.5: 37.7 (#153), Deepseek Coder v2: 32.3 (#212)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Expert | 1442 | 1181 |
| GPQA Diamond | 71.2% | — |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| Vectara Hallucination Rate | 9.8% | — |
| GPQA (HELM) | 60.5% | — |
| ARC (AI2) Challenge | — | 64.3% |
Multimodal Not comparable
Claude Haiku 4.5: 26.8 (#118), Deepseek Coder v2: —
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
Multilingual Claude Haiku 4.5 leads
Claude Haiku 4.5: 49.9 (#129), Deepseek Coder v2: 36.3 (#240)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Non-English | 1377 | 1182 |
| LMArena Chinese | 1417 | 1201 |
| LMArena French | 1408 | 1185 |
| LMArena German | 1375 | 1164 |
| LMArena Japanese | 1339 | 1126 |
| LMArena Korean | 1347 | 1104 |
| LMArena Russian | 1381 | 1188 |
| LMArena Spanish | 1420 | 1153 |
Instruction Following Claude Haiku 4.5 leads
Claude Haiku 4.5: 71.4 (#149), Deepseek Coder v2: 61.7 (#242)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Instruction Following | 1414 | 1180 |
| IFEval | 80.1% | — |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#92), Deepseek Coder v2: 37.0 (#224)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Longer Query | 1427 | 1219 |
Writing & Preference Claude Haiku 4.5 leads
Claude Haiku 4.5: 57.9 (#123), Deepseek Coder v2: 38.2 (#253)
| Benchmark | Claude Haiku 4.5 | Deepseek Coder v2 |
|---|---|---|
| LMArena Text | 1396 | 1191 |
| LMArena Creative Writing | 1372 | 1120 |
| LMArena Multi-Turn | 1409 | 1177 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Deepseek Coder v2?
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 35.9 on the Noometry Index.
Is Claude Haiku 4.5 or Deepseek Coder v2 better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 38.1 in the Noometry coding category.
How many benchmarks do Claude Haiku 4.5 and Deepseek Coder v2 share?
17 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Deepseek Coder v2 has 24.