Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 3 Pro Deep Think
80
Winner · 1/8 categoriesGLM-5V-Turbo
~58
0/8 categoriesGemini 3 Pro Deep Think· GLM-5V-Turbo
Pick Gemini 3 Pro Deep Think if you want the stronger benchmark profile. GLM-5V-Turbo only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Gemini 3 Pro Deep Think is clearly ahead on the aggregate, 80 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3 Pro Deep Think's sharpest advantage is in agentic, where it averages 78.1 against 58. The single biggest benchmark swing on the page is BrowseComp, 87% to 51.9%.
Gemini 3 Pro Deep Think is the reasoning model in the pair, while GLM-5V-Turbo is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 3 Pro Deep Think gives you the larger context window at 2M, compared with 200K for GLM-5V-Turbo.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | Gemini 3 Pro Deep Think | GLM-5V-Turbo |
|---|---|---|
| AgenticGemini 3 Pro Deep Think wins | ||
| Terminal-Bench 2.0 | 77% | — |
| BrowseComp | 87% | 51.9% |
| OSWorld-Verified | 73% | 62.3% |
| BrowseComp-VL | — | 51.9% |
| OSWorld | — | 62.3% |
| AndroidWorld | — | 75.7% |
| WebVoyager | — | 88.5% |
| Coding | ||
| HumanEval | 91% | — |
| SWE-bench Verified | 58% | — |
| LiveCodeBench | 58% | — |
| SWE-bench Pro | 63% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 95% | — |
| OfficeQA Pro | 95% | — |
| Design2Code | — | 94.8% |
| Flame-VLM-Code | — | 93.8% |
| Vision2Web | — | 31.0% |
| ImageMining | — | 30.7% |
| MMSearch | — | 72.9% |
| MMSearch-Plus | — | 30.0% |
| SimpleVQA | — | 78.2% |
| Facts-VLM | — | 58.6% |
| V* | — | 89.0% |
| Reasoning | ||
| MuSR | 93% | — |
| BBH | 95% | — |
| LongBench v2 | 94% | — |
| MRCRv2 | 96% | — |
| ARC-AGI-2 | 45.1% | — |
| Knowledge | ||
| MMLU | 99% | — |
| GPQA | 97% | — |
| SuperGPQA | 95% | — |
| MMLU-Pro | 81% | — |
| HLE | 32% | — |
| FrontierScience | 88% | — |
| SimpleQA | 95% | — |
| Instruction Following | ||
| IFEval | 89% | — |
| Multilingual | ||
| MGSM | 92% | — |
| MMLU-ProX | 85% | — |
| Mathematics | ||
| AIME 2023 | 99% | — |
| AIME 2024 | 99% | — |
| AIME 2025 | 98% | — |
| HMMT Feb 2023 | 95% | — |
| HMMT Feb 2024 | 97% | — |
| HMMT Feb 2025 | 96% | — |
| BRUMO 2025 | 96% | — |
| MATH-500 | 92% | — |
Gemini 3 Pro Deep Think is ahead overall, 80 to 58. The biggest single separator in this matchup is BrowseComp, where the scores are 87% and 51.9%.
Gemini 3 Pro Deep Think has the edge for agentic tasks in this comparison, averaging 78.1 versus 58. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.