Model comparison
Claude Opus 4 vs GLM-4.5-Air
Claude Opus 4 is the stronger model overall, scoring 43.1 to 38.9 on the Noometry Index. GLM-4.5-Air costs 71× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. Claude Opus 4 scores higher in 6 categories and GLM-4.5-Air in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Opus 4 leads 47.2 to 33.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 74.3% for Claude Opus 4 and 43% for GLM-4.5-Air.
- GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $15 / $75 for Claude Opus 4.
- Claude Opus 4 accepts more context: 200K tokens versus 131K.
- GLM-4.5-Air has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4 | GLM-4.5-Air | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 43.1 | 38.9 |
| Released | 2025-05-22 | 2025-07-20 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 32K | 98K |
| Input $ / M tokens | $15 | $0.20 |
| Output $ / M tokens | $75 | $1.10 |
| Results tracked | 56 | 27 |
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Category by category
Coding Claude Opus 4 leads
Claude Opus 4: 47.2 (#62), GLM-4.5-Air: 33.3 (#259)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| GSO | 6.9% | 2.9% |
| LMArena Coding | 1442 | 1397 |
| SWE-bench Verified | 70.7% | — |
| SWE-bench Verified (bash only) | 67.6% | — |
| Aider Polyglot | 72% | — |
| WeirdML | 43.7% | — |
| AlgoTune | 1.33 | — |
Agentic & Tool Use Not comparable
Claude Opus 4: 34.8 (#42), GLM-4.5-Air: —
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| Cybench | 38% | — |
| DeepResearch Bench | 46.8% | — |
| LMArena Search | 1127 | — |
| METR Time Horizons | 63.9% | — |
Reasoning Claude Opus 4 leads
Claude Opus 4: 27.3 (#121), GLM-4.5-Air: 24.1 (#166)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| Kagi LLM Benchmark | 74.3% | 43% |
| LMArena Hard Prompts | 1399 | 1379 |
| ForecastBench | 61.1 | 59.2 |
| ARC-AGI-2 | 8.6% | — |
| SimpleBench | 58.8% | — |
| ARC-AGI-1 | 35.7% | — |
| CritPt | 0.3% | — |
| EnigmaEval | 5.6% | — |
| DTBench | 81.6% | — |
| LMCA | 37.4% | — |
| Epoch Capabilities Index | 142.67 | — |
Math Claude Opus 4 leads
Claude Opus 4: 42.0 (#86), GLM-4.5-Air: 36.2 (#170)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| Omni-MATH | 61.6% | 39.1% |
| LMArena Math | 1390 | 1396 |
| OTIS Mock AIME 2024-2025 | 64.4% | — |
| MATH Level 5 | 85% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Claude Opus 4 leads
Claude Opus 4: 44.0 (#88), GLM-4.5-Air: 35.0 (#191)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| Humanity's Last Exam | 10.7% | 8.1% |
| MMLU-Pro | 87.5% | 76.2% |
| Vectara Hallucination Rate | 12% | 9.3% |
| GPQA (HELM) | 70.8% | 59.4% |
| LMArena Expert | 1386 | 1370 |
| GPQA Diamond | 76.3% | — |
| Confabulations | 15.9% | — |
Multimodal Not comparable
Claude Opus 4: 31.5 (#106), GLM-4.5-Air: —
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| LMArena Vision | 1192 | — |
| GeoBench | 49% | — |
| VPCT | 38% | — |
Multilingual Too close to call
Claude Opus 4: 48.8 (#138), GLM-4.5-Air: 49.1 (#135)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| LMArena Non-English | 1362 | 1366 |
| LMArena Chinese | 1386 | 1426 |
| LMArena French | 1372 | 1399 |
| LMArena German | 1391 | 1377 |
| LMArena Japanese | 1331 | 1348 |
| LMArena Korean | 1321 | 1308 |
| LMArena Russian | 1392 | 1373 |
| LMArena Spanish | 1389 | 1386 |
Instruction Following Claude Opus 4 leads
Claude Opus 4: 77.1 (#28), GLM-4.5-Air: 69.6 (#171)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| IFEval | 91.8% | 81.2% |
| LMArena Instruction Following | 1406 | 1354 |
Long Context GLM-4.5-Air leads
Claude Opus 4: 39.6 (#172), GLM-4.5-Air: 41.6 (#135)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| LMArena Longer Query | 1422 | 1366 |
| Fiction.LiveBench | 61.1% | — |
Writing & Preference Claude Opus 4 leads
Claude Opus 4: 61.2 (#89), GLM-4.5-Air: 55.9 (#139)
| Benchmark | Claude Opus 4 | GLM-4.5-Air |
|---|---|---|
| LMArena Text | 1377 | 1384 |
| LMArena Creative Writing | 1387 | 1343 |
| WildBench | 85.2% | 78.9% |
| LMArena Multi-Turn | 1396 | 1371 |
| Short-Story Creative Writing | 83.6% | — |
| EQ-Bench Creative Writing | 1580 | — |
Frequently asked questions
Is Claude Opus 4 better than GLM-4.5-Air?
Claude Opus 4 is the stronger model overall, scoring 43.1 to 38.9 on the Noometry Index. GLM-4.5-Air costs 71× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4 or GLM-4.5-Air?
GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; Claude Opus 4 lists at $15 and $75.
Is Claude Opus 4 or GLM-4.5-Air better for coding?
Claude Opus 4 scores higher on coding benchmarks: 47.2 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4 does, with 200K tokens against 131K.
How many benchmarks do Claude Opus 4 and GLM-4.5-Air share?
27 benchmarks have published results for both models. Claude Opus 4 has 56 scored results on Noometry and GLM-4.5-Air has 27.