Model comparison
Claude Opus 4 vs GLM-5.3-Flash
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 42.9 on the Noometry Index.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. Claude Opus 4 scores higher in 1 category and GLM-5.3-Flash in 9 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 43.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 64.4% for Claude Opus 4 and 93.9% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $15 / $75 for Claude Opus 4.
- GLM-5.3-Flash accepts more context: 1M tokens versus 200K.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4 | GLM-5.3-Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 42.9 | 49.6 |
| Released | 2025-05-22 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | 200K | 1M |
| Max output | 32K | 131K |
| Input $ / M tokens | $15 | $0.15 |
| Output $ / M tokens | $75 | $0.50 |
| Results tracked | 56 | 36 |
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Category by category
Coding GLM-5.3-Flash leads
Claude Opus 4: 47.8 (#55), GLM-5.3-Flash: 53.7 (#26)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| LMArena Coding | 1442 | 1506 |
| SWE-bench Verified | 70.7% | — |
| DeepSWE | — | 63.4% |
| FrontierCode | — | 31.8% |
| SWE-bench Verified (bash only) | 67.6% | — |
| Aider Polyglot | 72% | — |
| LMArena WebDev | — | 1614 |
| SciCode | — | 51.6% |
| GSO | 6.9% | — |
| WeirdML | 43.7% | — |
| ALE-Bench | — | 303.55 |
| AlgoTune | 1.33 | — |
Agentic & Tool Use Too close to call
Claude Opus 4: 34.5 (#39), GLM-5.3-Flash: 34.3 (#41)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | — | 52.8% |
| Cybench | 38% | — |
| DeepResearch Bench | 46.8% | — |
| GDP.pdf | — | 14% |
| LMArena Search | 1127 | — |
| METR Time Horizons | 63.9% | — |
Reasoning GLM-5.3-Flash leads
Claude Opus 4: 27.4 (#104), GLM-5.3-Flash: 31.7 (#69)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| CritPt | 0.3% | 15.4% |
| LMArena Hard Prompts | 1399 | 1490 |
| Epoch Capabilities Index | 142.67 | 151.9 |
| ARC-AGI-2 | 8.6% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 74.3% | — |
| ARC-AGI-1 | 35.7% | — |
| Chess Puzzles | — | 14% |
| EnigmaEval | 5.6% | — |
| Mystery Game Puzzles | — | 8% |
| DTBench | 81.6% | — |
| LMCA | 37.4% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 61.1 | — |
Math GLM-5.3-Flash leads
Claude Opus 4: 40.2 (#80), GLM-5.3-Flash: 53.1 (#38)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 64.4% | 93.9% |
| LMArena Math | 1391 | 1499 |
| FrontierMath (Tiers 1-3) | — | 55.8% |
| FrontierMath Tier 4 | — | 17.1% |
| ProofBench | — | 21% |
| Omni-MATH | 61.6% | — |
| MATH Level 5 | 85% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge GLM-5.3-Flash leads
Claude Opus 4: 43.9 (#82), GLM-5.3-Flash: 58.4 (#33)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 76.3% | 90.2% |
| LMArena Expert | 1384 | 1512 |
| Humanity's Last Exam | 10.7% | — |
| MMLU-Pro | 87.5% | — |
| Confabulations | 15.9% | — |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | 70.8% | — |
Multimodal GLM-5.3-Flash leads
Claude Opus 4: 30.9 (#101), GLM-5.3-Flash: 42.6 (#25)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1192 | 1304 |
| GeoBench | 49% | — |
| VPCT | 38% | — |
Multilingual GLM-5.3-Flash leads
Claude Opus 4: 49.0 (#133), GLM-5.3-Flash: 56.2 (#24)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1362 | 1462 |
| LMArena Chinese | 1386 | 1529 |
| LMArena French | 1370 | 1495 |
| LMArena German | 1391 | 1457 |
| LMArena Japanese | 1332 | 1420 |
| LMArena Korean | 1318 | 1443 |
| LMArena Russian | 1392 | 1472 |
| LMArena Spanish | 1388 | 1471 |
Instruction Following Too close to call
Claude Opus 4: 77.3 (#26), GLM-5.3-Flash: 77.8 (#17)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1406 | 1480 |
| IFEval | 91.8% | — |
Long Context GLM-5.3-Flash leads
Claude Opus 4: 39.5 (#167), GLM-5.3-Flash: 45.3 (#41)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1422 | 1479 |
| Fiction.LiveBench | 61.1% | — |
Writing & Preference GLM-5.3-Flash leads
Claude Opus 4: 61.4 (#85), GLM-5.3-Flash: 65.4 (#49)
| Benchmark | Claude Opus 4 | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1377 | 1471 |
| LMArena Creative Writing | 1386 | 1440 |
| LMArena Multi-Turn | 1396 | 1471 |
| Short-Story Creative Writing | 83.6% | — |
| EQ-Bench Creative Writing | 1580 | — |
| WildBench | 85.2% | — |
Frequently asked questions
Is Claude Opus 4 better than GLM-5.3-Flash?
GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 42.9 on the Noometry Index.
Which is cheaper, Claude Opus 4 or GLM-5.3-Flash?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Claude Opus 4 lists at $15 and $75.
Is Claude Opus 4 or GLM-5.3-Flash better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 47.8 in the Noometry coding category.
Which has the bigger context window?
GLM-5.3-Flash does, with 1M tokens against 200K.
How many benchmarks do Claude Opus 4 and GLM-5.3-Flash share?
22 benchmarks have published results for both models. Claude Opus 4 has 56 scored results on Noometry and GLM-5.3-Flash has 36.