Model comparison
Claude 3.5 Haiku vs GLM-4.5
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.2 on the Noometry Index.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. Claude 3.5 Haiku scores higher in 1 category and GLM-4.5 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.5 leads 39.0 to 14.7.
- The biggest single-benchmark swing is Confabulations: 36.7% for Claude 3.5 Haiku and 11.3% for GLM-4.5.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| Claude 3.5 Haiku | GLM-4.5 | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 29.2 | 42.0 |
| Released | 2024-10-22 | 2025-07-27 |
| Weights | Proprietary | Open |
| Context window | — | 131K |
| Max output | — | 98K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $2.20 |
| Results tracked | 49 | 27 |
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Category by category
Coding GLM-4.5 leads
Claude 3.5 Haiku: 32.9 (#265), GLM-4.5: 41.4 (#125)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| WeirdML | 30.7% | 40.6% |
| LMArena Coding | 1286 | 1434 |
| SWE-bench Verified (bash only) | — | 54.2% |
| Aider Polyglot | 28% | — |
| SciCode | 27.4% | — |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 51.4% | — |
| BigCodeBench Complete | 59% | — |
| CadEval | 32% | — |
| ALE-Bench | — | 344.82 |
| AlgoTune | — | 1.52 |
Agentic & Tool Use Not comparable
Claude 3.5 Haiku: 28.0 (#95), GLM-4.5: —
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| BALROG | 19.3% | — |
Reasoning GLM-4.5 leads
Claude 3.5 Haiku: 17.7 (#290), GLM-4.5: 28.6 (#100)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| LMArena Hard Prompts | 1251 | 1429 |
| Kagi LLM Benchmark | — | 57.9% |
| CritPt | 0% | — |
| LiveBench Reasoning | 28.1% | — |
| DTBench | 56.7% | — |
| LiveBench Data Analysis | 48.5% | — |
| Epoch Capabilities Index | 127.15 | — |
| LiveBench | 43.5% | — |
Math GLM-4.5 leads
Claude 3.5 Haiku: 14.7 (#300), GLM-4.5: 39.0 (#116)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| LMArena Math | 1244 | 1427 |
| OTIS Mock AIME 2024-2025 | 4.3% | — |
| Omni-MATH | 22.4% | — |
| LiveBench Math | 35.5% | — |
| MATH Level 5 | 46.4% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge GLM-4.5 leads
Claude 3.5 Haiku: 18.7 (#281), GLM-4.5: 35.9 (#179)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| Confabulations | 36.7% | 11.3% |
| LMArena Expert | 1208 | 1433 |
| GPQA Diamond | 38.1% | — |
| Humanity's Last Exam | — | 8.3% |
| MMLU-Pro | 60.5% | — |
| GPQA (HELM) | 36.3% | — |
| MMLU | 74.3% | — |
Multimodal Not comparable
Claude 3.5 Haiku: 26.8 (#117), GLM-4.5: —
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| LMArena Vision | 1092 | — |
| GeoBench | 34% | — |
Multilingual GLM-4.5 leads
Claude 3.5 Haiku: 40.0 (#218), GLM-4.5: 52.8 (#77)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| LMArena Non-English | 1238 | 1417 |
| LMArena Chinese | 1229 | 1465 |
| LMArena French | 1264 | 1418 |
| LMArena German | 1237 | 1407 |
| LMArena Japanese | 1175 | 1415 |
| LMArena Korean | 1173 | 1380 |
| LMArena Russian | 1253 | 1414 |
| LMArena Spanish | 1261 | 1454 |
Instruction Following GLM-4.5 leads
Claude 3.5 Haiku: 62.9 (#234), GLM-4.5: 74.1 (#104)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| LMArena Instruction Following | 1241 | 1404 |
| LiveBench Instruction Following | 61.9% | — |
| IFEval | 79.2% | — |
Long Context Too close to call
Claude 3.5 Haiku: 38.3 (#200), GLM-4.5: 38.2 (#201)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| LMArena Longer Query | 1261 | 1412 |
| Fiction.LiveBench | — | 58.3% |
Writing & Preference GLM-4.5 leads
Claude 3.5 Haiku: 42.7 (#234), GLM-4.5: 57.5 (#127)
| Benchmark | Claude 3.5 Haiku | GLM-4.5 |
|---|---|---|
| LMArena Text | 1255 | 1430 |
| LMArena Creative Writing | 1233 | 1395 |
| Short-Story Creative Writing | 73.5% | 73.4% |
| EQ-Bench Creative Writing | 1146 | 1343 |
| LMArena Multi-Turn | 1265 | 1415 |
| WildBench | 76% | — |
| LiveBench Language | 35.4% | — |
Frequently asked questions
Is Claude 3.5 Haiku better than GLM-4.5?
GLM-4.5 is the stronger model overall, scoring 42.0 to 29.2 on the Noometry Index.
Is Claude 3.5 Haiku or GLM-4.5 better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.4 versus 32.9 in the Noometry coding category.
How many benchmarks do Claude 3.5 Haiku and GLM-4.5 share?
21 benchmarks have published results for both models. Claude 3.5 Haiku has 49 scored results on Noometry and GLM-4.5 has 27.