Model comparison
Claude Opus 4.7 vs GLM-5.3-Flash
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 42× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.
Last verified . 35 shared benchmarks.
Summary
- They share 35 benchmarks with published results for both. Claude Opus 4.7 scores higher in 9 categories and GLM-5.3-Flash in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Claude Opus 4.7 leads 47.9 to 34.2.
- The biggest single-benchmark swing is ProofBench: 54% for Claude Opus 4.7 and 21% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.7 | GLM-5.3-Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 58.3 | 51.8 |
| Released | 2026-04-14 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | 1M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $5 | $0.15 |
| Output $ / M tokens | $25 | $0.50 |
| Results tracked | 66 | 40 |
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Category by category
Coding Claude Opus 4.7 leads
Claude Opus 4.7: 59.6 (#13), GLM-5.3-Flash: 53.1 (#31)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| FrontierCode | 38.5% | 31.8% |
| LMArena WebDev | 1558 | 1609 |
| SciCode | 54.5% | 51.6% |
| LMArena Coding | 1518 | 1508 |
| ALE-Bench | 1,323 | 303.55 |
| SWE-bench Verified | 83.5% | — |
| DeepSWE | — | 63.4% |
| CursorBench | — | 36.8% |
| FrontierSWE | — | 18.1% |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |
Agentic & Tool Use Claude Opus 4.7 leads
Claude Opus 4.7: 47.9 (#10), GLM-5.3-Flash: 34.2 (#47)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | 49.2% | 52.8% |
| GDP.pdf | 21% | 14% |
| Terminal-Bench | 80.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |
Reasoning Claude Opus 4.7 leads
Claude Opus 4.7: 53.8 (#29), GLM-5.3-Flash: 48.0 (#42)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| ARC-AGI-2 | 75.8% | 65.8% |
| ARC-AGI-1 | 93.5% | 91% |
| CritPt | 12% | 15.4% |
| Chess Puzzles | 30% | 14% |
| LMArena Hard Prompts | 1506 | 1491 |
| Mystery Game Puzzles | 28% | 8% |
| Epoch Capabilities Index | 156.25 | 151.88 |
| SimpleBench | 61.7% | — |
| Kagi LLM Benchmark | 80.7% | — |
| NYT Connections (extended) | 39% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| DTBench | 94.7% | — |
| LMCA | 52.2% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 60.3 | — |
Math Claude Opus 4.7 leads
Claude Opus 4.7: 66.7 (#26), GLM-5.3-Flash: 53.3 (#47)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 70.2% | 55.8% |
| FrontierMath Tier 4 | 31.7% | 17.1% |
| OTIS Mock AIME 2024-2025 | 97.8% | 93.9% |
| ProofBench | 54% | 21% |
| LMArena Math | 1499 | 1500 |
| MathArena Final-Answer Competitions | 73.6% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
Knowledge Claude Opus 4.7 leads
Claude Opus 4.7: 62.6 (#23), GLM-5.3-Flash: 58.4 (#36)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 90.2% | 90.2% |
| LMArena Expert | 1521 | 1513 |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
| Vectara Hallucination Rate | 12% | — |
Multimodal GLM-5.3-Flash leads
Claude Opus 4.7: 41.2 (#38), GLM-5.3-Flash: 42.8 (#27)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1316 | 1296 |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |
Multilingual Claude Opus 4.7 leads
Claude Opus 4.7: 57.3 (#10), GLM-5.3-Flash: 56.0 (#25)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1480 | 1462 |
| LMArena Chinese | 1531 | 1527 |
| LMArena French | 1503 | 1496 |
| LMArena German | 1495 | 1470 |
| LMArena Japanese | 1472 | 1429 |
| LMArena Korean | 1464 | 1446 |
| LMArena Russian | 1494 | 1469 |
| LMArena Spanish | 1495 | 1471 |
Instruction Following Too close to call
Claude Opus 4.7: 78.4 (#10), GLM-5.3-Flash: 77.5 (#20)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1498 | 1478 |
Long Context Too close to call
Claude Opus 4.7: 46.2 (#25), GLM-5.3-Flash: 45.4 (#39)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1505 | 1482 |
Writing & Preference Claude Opus 4.7 leads
Claude Opus 4.7: 75.1 (#8), GLM-5.3-Flash: 65.3 (#50)
| Benchmark | Claude Opus 4.7 | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1490 | 1471 |
| LMArena Creative Writing | 1486 | 1442 |
| LMArena Multi-Turn | 1505 | 1467 |
| EQ-Bench Creative Writing | 1914 | — |
| EQ-Bench 4 | 1311 | — |
Frequently asked questions
Is Claude Opus 4.7 better than GLM-5.3-Flash?
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 42× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.7 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 4.7 lists at $5 and $25.
Is Claude Opus 4.7 or GLM-5.3-Flash better for coding?
Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 53.1 in the Noometry coding category.
Which has the bigger context window?
Both accept 1M tokens.
How many benchmarks do Claude Opus 4.7 and GLM-5.3-Flash share?
35 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and GLM-5.3-Flash has 40.