Gemini 4 Argon vs GLM 5.3 Flash
Gemini 4 Argon 
GLM 5.3 Flash Verdict
- Gemini 4 Argon (high) leads on quality: 70.0 vs 62.2.
- Gemini 4 Argon (high) is stronger in agents & tools, coding, composite, human preference, knowledge, maths, reasoning.
- GLM 5.3 Flash is stronger in long context, multimodal.
- GLM 5.3 Flash is 17× cheaper ($0.238 vs $4.00 per 1M blended).
| Metric | Gemini 4 Argon (high) | GLM 5.3 Flash |
|---|---|---|
| BenchLeader Index | 70.0 | 62.2 |
| Agents & tools score | 67.5 | 62.7 |
| Coding score | 72.1 | 63.4 |
| Composite score | 89.2 | 58.6 |
| Human preference score | 73.2 | 67.0 |
| Knowledge score | 75.7 | 65.0 |
| Long context score | 65.0 | 65.2 |
| Maths score | 71.9 | 69.0 |
| Reasoning score | 82.0 | 67.0 |
| Multimodal score | – | 64.2 |
| Blended price $/M | $4.00 | $0.238 |
| Output speed | – | 53 tok/s |
| Time to first answer | – | 41.0 s |
| Context window | 1M | 1M |
| SciCode | 61.8% | 51.6% |
| APEX-Agents | – | 52.8% |
| Epoch Capabilities Index | – | 151.9 |
| LMArena Text | 1525 | 1475 |
| LMArena Hard Prompts | 1551 | 1501 |
| LMArena Coding | 1562 | 1525 |
| LMArena WebDev | 1678 | 1609 |
| LMArena Vision | – | 1296 |
| LMArena Agent | 9.3 | -1 |
| LiveBench | – | 71.6% |
| LiveBench Reasoning | – | 77.6% |
| LiveBench Coding | – | 79.0% |
| LiveBench Agentic Coding | – | 56.8% |
| LiveBench Mathematics | – | 81.2% |
| LiveBench Data Analysis | – | 76.4% |
| LiveBench Language | – | 77.3% |
| LiveBench Instruction Following | – | 52.8% |
| AA Intelligence Index v4.3.2 | 52.6 | 41.8 |
| AA-LCR | 79.7% | 80.0% |
| AA-Omniscience | 42.4 | 7.5 |
| GPQA Diamond (AA) | – | 91.2% |
| Humanity's Last Exam (AA) | 57.1% | 39.9% |
| SciCode (AA) | 61.8% | 51.6% |
| IOI | 100.0% | – |
| LegalBench | 88.3% | – |
| Vals Index | 68.9 | – |
| CritPt | 27.1% | 15.4% |
| GDPval-AA v2.1 | 56.3% | 57.2% |
| τ³-Banking (AA) | – | 47.2% |
| ITBench SRE (AA) | – | 51.2% |
| BioMysteryBench | 76.3% | – |
| Code Migration | 68.2% | – |
| CUA-bench | 4.8% | – |
| CyberBench | 77.9% | – |
| Excel Modeling Benchmark | 75.2% | – |
| Finance Agent v2 | 65.4% | – |
| Harvey's Legal Agent Benchmark | 19.6% | – |
| Legal Research Bench | 54.8% | – |
| MedCode | 58.8% | – |
| MedScribe | 87.4% | – |
| MysteryMechanism | 45.5% | – |
| ProgramBench | 2.5% | – |
| Public Benefits Bench | 69.8% | – |
| SAGE | 53.6% | – |
| SREBench | 44.3% | – |
| Tax Agent Bench | 76.2% | – |
| Terminal-Bench 4.0 (Vals) | 57.6% | – |
| Terminal-Bench Science | 44.3% | – |
| Vibe Code Bench v1.1 | 91.9% | – |
| LMArena Maths | 1528 | 1502 |
| LMArena Creative Writing | 1519 | 1435 |
| LMArena Instruction Following | 1529 | 1472 |
| LMArena Multi-turn | 1553 | 1472 |
| LMArena Longer Queries | 1545 | 1481 |
| FrontierSWE | 55.0% | – |
| BTF-3 | – | 14.9% |
| Terminal-Bench 4.0 (AA) | 57.1% | 32.8% |
| Terminal-Bench 2.1 (AA) | – | 84.3% |
| AutomationBench | 77.5% | 60.4% |
| GDP.pdf | 21.8% | 15.4% |
| MLCR | – | 51.1% |
| Harvey LAB | – | 0.8% |
| EnterpriseOps-Gym | – | 33.2% |
| AA-Omniscience: accuracy | 49.9% | 27.5% |
| AA-Omniscience: non-hallucination | 84.9% | 72.4% |
| AA-Briefcase v1.1 | 1488 | 1454 |
| AA Openness Index | – | 44.4 |
Data as of 2026-10-11. Best configuration of each model; every score links to its source on the model pages.
Gemini 4 Argon vs GLM 5.3 Flash: questions
- Is Gemini 4 Argon better than GLM 5.3 Flash?
- Gemini 4 Argon (high) leads on quality: 70.0 vs 62.2. The BenchLeader Index combines every independent quality benchmark; Gemini 4 Argon (high) is ahead overall as of 2026-10-11, but check the category scores for your use.
- Is Gemini 4 Argon better than GLM 5.3 Flash for coding?
- Gemini 4 Argon scores higher in coding (72 vs 63 on the category index, where 50 is average).
- Is Gemini 4 Argon better than GLM 5.3 Flash for agentic tasks?
- Gemini 4 Argon scores higher in agentic tasks (68 vs 63 on the category index, where 50 is average).
- Which is cheaper, Gemini 4 Argon or GLM 5.3 Flash?
- GLM 5.3 Flash is cheaper: $0.238 against $4.00 per million tokens, blended at three input tokens per output token.
- Which has the larger context window?
- Both accept 1M tokens of context.