Model comparison
Claude Haiku 4.5 vs Llama 2-13B
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 29.6 on the Noometry Index.
Last verified . 20 shared benchmarks.
MetaSummary
- They share 20 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 8 categories and Llama 2-13B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Haiku 4.5 leads 57.9 to 29.8.
- The biggest single-benchmark swing is DTBench: 73.6% for Claude Haiku 4.5 and 42.2% for Llama 2-13B.
- Llama 2-13B has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Llama 2-13B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 39.5 | 29.6 |
| Released | 2025-10-15 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | 200K | — |
| Max output | 64K | — |
| Input $ / M tokens | $1 | — |
| Output $ / M tokens | $5 | — |
| Results tracked | 53 | 32 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.0 (#78), Llama 2-13B: 30.9 (#291)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1453 | 1062 |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| SciCode | 43.3% | — |
| WeirdML | 45.4% | — |
| ALE-Bench | 653.48 | — |
Agentic & Tool Use Not comparable
Claude Haiku 4.5: 33.6 (#52), Llama 2-13B: —
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| 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 Claude Haiku 4.5 leads
Claude Haiku 4.5: 15.1 (#320), Llama 2-13B: 12.8 (#337)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| Chess Puzzles | 8% | 0% |
| LMArena Hard Prompts | 1420 | 1051 |
| DTBench | 73.6% | 42.2% |
| Epoch Capabilities Index | 142.41 | 106.17 |
| ARC-AGI-2 | 4% | — |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| CritPt | 0% | — |
| LMCA | 30.9% | — |
| BIG-Bench Hard | — | 58.2% |
| ForecastBench | 61.4 | — |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.9 (#78), Llama 2-13B: 31.1 (#229)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| LMArena Math | 1396 | 1065 |
| 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 | — | 36.9% |
Knowledge Claude Haiku 4.5 leads
Claude Haiku 4.5: 37.7 (#153), Llama 2-13B: 28.1 (#249)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1442 | 1030 |
| GPQA Diamond | 71.2% | — |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| Vectara Hallucination Rate | 9.8% | — |
| GPQA (HELM) | 60.5% | — |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |
Multimodal Not comparable
Claude Haiku 4.5: 26.8 (#118), Llama 2-13B: —
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
| ScienceQA | — | 55.8% |
Multilingual Claude Haiku 4.5 leads
Claude Haiku 4.5: 49.9 (#129), Llama 2-13B: 26.5 (#279)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1377 | 1024 |
| LMArena Chinese | 1417 | 1001 |
| LMArena French | 1408 | 1044 |
| LMArena German | 1375 | 1009 |
| LMArena Japanese | 1339 | 894 |
| LMArena Korean | 1347 | 953 |
| LMArena Russian | 1381 | 1055 |
| LMArena Spanish | 1420 | 1087 |
Instruction Following Claude Haiku 4.5 leads
Claude Haiku 4.5: 71.4 (#149), Llama 2-13B: 53.3 (#287)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1414 | 1045 |
| IFEval | 80.1% | — |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#92), Llama 2-13B: 32.3 (#269)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1427 | 1064 |
Writing & Preference Claude Haiku 4.5 leads
Claude Haiku 4.5: 57.9 (#123), Llama 2-13B: 29.8 (#289)
| Benchmark | Claude Haiku 4.5 | Llama 2-13B |
|---|---|---|
| LMArena Text | 1396 | 1084 |
| LMArena Creative Writing | 1372 | 1047 |
| LMArena Multi-Turn | 1409 | 1050 |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Llama 2-13B?
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 29.6 on the Noometry Index.
Is Claude Haiku 4.5 or Llama 2-13B better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 30.9 in the Noometry coding category.
How many benchmarks do Claude Haiku 4.5 and Llama 2-13B share?
20 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Llama 2-13B has 32.