Model comparison
Claude 3.5 Haiku vs GLM-5.1
GLM-5.1 is the stronger model overall, scoring 47.6 to 28.9 on the Noometry Index.
Last verified . 25 shared benchmarks.
Summary
- They share 25 benchmarks with published results for both. Claude 3.5 Haiku scores higher in 1 category and GLM-5.1 in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.1 leads 55.0 to 18.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 4.3% for Claude 3.5 Haiku and 93.3% for GLM-5.1.
- GLM-5.1 has downloadable open weights; the other is API-only.
Side by side
| Claude 3.5 Haiku | GLM-5.1 | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 28.9 | 47.6 |
| Released | 2024-10-22 | 2026-04-07 |
| Weights | Proprietary | Open |
| Context window | — | 200K |
| Max output | — | 131K |
| Input $ / M tokens | — | $1.40 |
| Output $ / M tokens | — | $4.40 |
| Results tracked | 49 | 41 |
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Category by category
Coding GLM-5.1 leads
Claude 3.5 Haiku: 32.6 (#258), GLM-5.1: 48.5 (#52)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| SciCode | 27.4% | 43.8% |
| WeirdML | 30.7% | 57.1% |
| LMArena Coding | 1287 | 1486 |
| SWE-bench Verified | — | 74.2% |
| Aider Polyglot | 28% | — |
| LMArena WebDev | — | 1509 |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 51.4% | — |
| BigCodeBench Complete | 59% | — |
| CadEval | 32% | — |
| ALE-Bench | — | 887.1 |
Agentic & Tool Use Claude 3.5 Haiku leads
Claude 3.5 Haiku: 27.7 (#90), GLM-5.1: 24.8 (#106)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| APEX-Agents | — | 40.9% |
| BALROG | 19.3% | — |
| ExploitBench | — | 18.1% |
| GBAEval | — | 0% |
| Vending-Bench 2 | — | 5,634 |
Reasoning GLM-5.1 leads
Claude 3.5 Haiku: 17.1 (#286), GLM-5.1: 38.2 (#57)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| CritPt | 0% | 4.6% |
| LMArena Hard Prompts | 1251 | 1472 |
| Epoch Capabilities Index | 127.15 | 149.86 |
| SimpleBench | — | 55.1% |
| NYT Connections (extended) | — | 77.7% |
| Chess Puzzles | — | 19% |
| Thematic Generalization | — | 69.8% |
| LiveBench Reasoning | 28.1% | — |
| DTBench | 56.7% | — |
| LiveBench Data Analysis | 48.5% | — |
| LiveBench | 43.5% | — |
Math GLM-5.1 leads
Claude 3.5 Haiku: 13.7 (#294), GLM-5.1: 49.0 (#48)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 4.3% | 93.3% |
| LMArena Math | 1244 | 1472 |
| FrontierMath (Feb 2025 set) | 0.3% | 33.4% |
| FrontierMath (Tiers 1-3) | — | 36.8% |
| MathArena Final-Answer Competitions | — | 67.1% |
| ProofBench | — | 22.2% |
| Omni-MATH | 22.4% | — |
| LiveBench Math | 35.5% | — |
| MATH Level 5 | 46.4% | — |
| FrontierMath Tier 4 (v1) | — | 12.5% |
Knowledge GLM-5.1 leads
Claude 3.5 Haiku: 18.7 (#276), GLM-5.1: 55.0 (#45)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| GPQA Diamond | 38.1% | 89.9% |
| LMArena Expert | 1208 | 1477 |
| SimpleQA Verified | — | 34% |
| MMLU-Pro | 60.5% | — |
| Confabulations | 36.7% | — |
| GPQA (HELM) | 36.3% | — |
| MMLU | 74.3% | — |
Multimodal Not comparable
Claude 3.5 Haiku: 26.3 (#113), GLM-5.1: —
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| LMArena Vision | 1092 | — |
| GeoBench | 34% | — |
Multilingual GLM-5.1 leads
Claude 3.5 Haiku: 40.2 (#213), GLM-5.1: 55.2 (#34)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| LMArena Non-English | 1238 | 1448 |
| LMArena Chinese | 1229 | 1516 |
| LMArena French | 1262 | 1478 |
| LMArena German | 1237 | 1466 |
| LMArena Japanese | 1175 | 1436 |
| LMArena Korean | 1172 | 1423 |
| LMArena Russian | 1253 | 1453 |
| LMArena Spanish | 1261 | 1467 |
Instruction Following GLM-5.1 leads
Claude 3.5 Haiku: 63.1 (#229), GLM-5.1: 76.5 (#41)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| LMArena Instruction Following | 1241 | 1451 |
| LiveBench Instruction Following | 61.9% | — |
| IFEval | 79.2% | — |
Long Context GLM-5.1 leads
Claude 3.5 Haiku: 38.3 (#195), GLM-5.1: 44.9 (#51)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| LMArena Longer Query | 1261 | 1467 |
Writing & Preference GLM-5.1 leads
Claude 3.5 Haiku: 42.9 (#228), GLM-5.1: 67.2 (#29)
| Benchmark | Claude 3.5 Haiku | GLM-5.1 |
|---|---|---|
| LMArena Text | 1255 | 1462 |
| LMArena Creative Writing | 1233 | 1454 |
| EQ-Bench Creative Writing | 1146 | 1592 |
| LMArena Multi-Turn | 1265 | 1473 |
| Short-Story Creative Writing | 73.5% | — |
| WildBench | 76% | — |
| LiveBench Language | 35.4% | — |
Frequently asked questions
Is Claude 3.5 Haiku better than GLM-5.1?
GLM-5.1 is the stronger model overall, scoring 47.6 to 28.9 on the Noometry Index.
Is Claude 3.5 Haiku or GLM-5.1 better for coding?
GLM-5.1 scores higher on coding benchmarks: 48.5 versus 32.6 in the Noometry coding category.
How many benchmarks do Claude 3.5 Haiku and GLM-5.1 share?
25 benchmarks have published results for both models. Claude 3.5 Haiku has 49 scored results on Noometry and GLM-5.1 has 41.