Claude Opus 4.7 vs GLM 5.3
Claude Opus 4.7 
GLM 5.3 Verdict
- Claude Opus 4.7 leads on quality: 65.6 vs 60.0.
- Claude Opus 4.7 is stronger in agents & tools, composite, human preference, instruction following, knowledge, long context, maths, multimodal.
- GLM 5.3 (max) is stronger in coding, reasoning.
- GLM 5.3 (max) is 4.7× cheaper ($2.15 vs $10.00 per 1M blended).
| Metric | Claude Opus 4.7 | GLM 5.3 (max) |
|---|---|---|
| BenchLeader Index | 65.6 | 60.0 |
| Agents & tools score | 69.4 | 52.9 |
| Coding score | 64.8 | 65.2 |
| Composite score | 80.4 | – |
| Human preference score | 69.1 | 68.6 |
| Instruction following score | 58.7 | – |
| Knowledge score | 66.5 | 55.8 |
| Long context score | 65.9 | – |
| Maths score | 65.4 | 60.0 |
| Multimodal score | 65.7 | – |
| Reasoning score | 66.6 | 66.9 |
| Blended price $/M | $10.00 | $2.15 |
| Output speed | 43 tok/s | 56 tok/s |
| Time to first answer | 21.7 s | 37.4 s |
| Context window | 1M | 1.3M |
| GPQA Diamond | – | 90.9% |
| FrontierMath Tiers 1–3 | – | 68.8% |
| FrontierMath Tier 4 | – | 29.3% |
| OTIS Mock AIME | – | 91.1% |
| SimpleQA Verified | – | 41.0% |
| Humanity's Last Exam | 36.2% | – |
| Terminal-Bench | 80.2% | 41.8% |
| SimpleBench | 61.7% | – |
| SciCode | – | 56.5% |
| WeirdML | 76.4% | 75.4% |
| FrontierCode | 38.5% | – |
| ProofBench | – | 49.0% |
| GSO-Bench | 44.1% | – |
| Epoch Capabilities Index | 156.3 | – |
| LMArena Text | 1495 | 1482 |
| LMArena Hard Prompts | 1519 | 1507 |
| LMArena Coding | 1547 | 1528 |
| LMArena WebDev | 1557 | 1613 |
| LMArena Vision | 1317 | – |
| LMArena Agent | – | 2.6 |
| AA Intelligence Index | 40.7 | – |
| IFBench | 58.6% | – |
| AA-LCR | 78.7% | – |
| MMMU-Pro | 78.8% | – |
| AA-Omniscience | 27.3 | – |
| Terminal-Bench Hard | 51.5% | – |
| GPQA Diamond (AA) | 91.4% | – |
| Humanity's Last Exam (AA) | 42.3% | – |
| τ²-Bench Telecom (AA) | 88.6% | – |
| AIME (Vals) | 96.3% | – |
| LiveCodeBench | 85.1% | 80.5% |
| MMLU-Pro | 89.9% | 86.8% |
| IOI | 47.1% | – |
| LegalBench | 85.3% | 84.8% |
| CorpFin | 66.1% | – |
| TaxEval | 75.3% | 72.4% |
| Terminal-Bench 2.1 (Vals) | 68.5% | 71.5% |
| SWE-bench (Vals) | 82.0% | 95.4% |
| GPQA Diamond (Vals) | 90.2% | 88.1% |
| Vals Index | 56.1 | 57.0 |
| HiL-Bench | 41.7% | – |
| EQ-Bench 4 | 1311 | – |
| Kagi LLM Benchmark | 73.3% | – |
Data as of 2026-09-10. Best configuration of each model; every score links to its source on the model pages.
Claude Opus 4.7 vs GLM 5.3: questions
- Is Claude Opus 4.7 better than GLM 5.3?
- Claude Opus 4.7 leads on quality: 65.6 vs 60.0. The BenchLeader Index combines every independent quality benchmark; Claude Opus 4.7 is ahead overall as of 2026-09-10, but check the category scores for your use.
- Is Claude Opus 4.7 better than GLM 5.3 for coding?
- GLM 5.3 scores higher in coding (65 vs 65 on the category index, where 50 is average).
- Is Claude Opus 4.7 better than GLM 5.3 for agentic tasks?
- Claude Opus 4.7 scores higher in agentic tasks (69 vs 53 on the category index, where 50 is average).
- Which is cheaper, Claude Opus 4.7 or GLM 5.3?
- GLM 5.3 is cheaper: $2.15 against $10.00 per million tokens, blended at three input tokens per output token.
- Which is faster, Claude Opus 4.7 or GLM 5.3?
- GLM 5.3 streams faster: 56 against 43 output tokens per second.
- Which has the larger context window?
- GLM 5.3 accepts more context: 1.3M against 1M tokens.