Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Gemini 3 Flash
66
Winner · 0/8 categoriesGLM-5V-Turbo
~58
1/8 categoriesGemini 3 Flash· GLM-5V-Turbo
Pick Gemini 3 Flash if you want the stronger benchmark profile. GLM-5V-Turbo only becomes the better choice if agentic is the priority.
Gemini 3 Flash is clearly ahead on the aggregate, 66 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5V-Turbo is also the more expensive model on tokens at $1.20 input / $4.00 output per 1M tokens, versus $0.50 input / $3.00 output per 1M tokens for Gemini 3 Flash. Gemini 3 Flash gives you the larger context window at 1M, 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 Flash | GLM-5V-Turbo |
|---|---|---|
| AgenticGLM-5V-Turbo wins | ||
| Terminal-Bench 2.0 | 56% | — |
| BrowseComp | 66% | 51.9% |
| OSWorld-Verified | 53% | 62.3% |
| BrowseComp-VL | — | 51.9% |
| OSWorld | — | 62.3% |
| AndroidWorld | — | 75.7% |
| WebVoyager | — | 88.5% |
| Coding | ||
| HumanEval | 62% | — |
| SWE-bench Verified | 44% | — |
| LiveCodeBench | 36% | — |
| SWE-bench Pro | 44% | — |
| SWE-Rebench | 52.5% | — |
| Multimodal & Grounded | ||
| MMMU-Pro | 80% | — |
| OfficeQA Pro | 79% | — |
| 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 | 65% | — |
| BBH | 84% | — |
| LongBench v2 | 75% | — |
| MRCRv2 | 76% | — |
| Knowledge | ||
| MMLU | 70% | — |
| GPQA | 69% | — |
| SuperGPQA | 67% | — |
| MMLU-Pro | 72% | — |
| HLE | 6% | — |
| FrontierScience | 65% | — |
| SimpleQA | 67% | — |
| Instruction Following | ||
| IFEval | 85% | — |
| Multilingual | ||
| MGSM | 85% | — |
| MMLU-ProX | 78% | — |
| Mathematics | ||
| AIME 2023 | 70% | — |
| AIME 2024 | 72% | — |
| AIME 2025 | 71% | — |
| HMMT Feb 2023 | 66% | — |
| HMMT Feb 2024 | 68% | — |
| HMMT Feb 2025 | 67% | — |
| BRUMO 2025 | 69% | — |
| MATH-500 | 80% | — |
Gemini 3 Flash is ahead overall, 66 to 58. The biggest single separator in this matchup is BrowseComp, where the scores are 66% and 51.9%.
GLM-5V-Turbo has the edge for agentic tasks in this comparison, averaging 58 versus 57.5. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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