Model comparison
Gemini 3.1 Pro Preview vs GLM-5.3-Flash
Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 19× less per token, which makes it the better buy when Gemini 3.1 Pro Preview's lead doesn't matter for your workload.
Last verified . 35 shared benchmarks.
Summary
- They share 35 benchmarks with published results for both. Gemini 3.1 Pro Preview scores higher in 7 categories and GLM-5.3-Flash in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.1 Pro Preview leads 71.7 to 48.0.
- The biggest single-benchmark swing is DeepSWE: 11.7% for Gemini 3.1 Pro Preview and 63.4% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $2 / $12 for Gemini 3.1 Pro Preview.
- Gemini 3.1 Pro Preview accepts more context: 1.05M tokens versus 1M.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Gemini 3.1 Pro Preview | GLM-5.3-Flash | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 56.7 | 51.8 |
| Released | 2026-02-19 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 1M |
| Max output | 66K | 131K |
| Input $ / M tokens | $2 | $0.15 |
| Output $ / M tokens | $12 | $0.50 |
| Results tracked | 71 | 40 |
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Category by category
Coding GLM-5.3-Flash leads
Gemini 3.1 Pro Preview: 42.5 (#99), GLM-5.3-Flash: 53.1 (#31)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| DeepSWE | 11.7% | 63.4% |
| LMArena WebDev | 1447 | 1609 |
| SciCode | 58.9% | 51.6% |
| LMArena Coding | 1484 | 1508 |
| ALE-Bench | 1,161 | 303.55 |
| SWE-bench Verified | 75.6% | — |
| FrontierCode | — | 31.8% |
| CursorBench | — | 36.8% |
| FrontierSWE | — | 18.1% |
| GSO | 22.6% | — |
| WeirdML | 72.1% | — |
| MirrorCode | 8.9% | — |
| AlgoTune | 2.02 | — |
Agentic & Tool Use Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 37.7 (#34), GLM-5.3-Flash: 34.2 (#47)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | 35.3% | 52.8% |
| GDP.pdf | 17% | 14% |
| Terminal-Bench | 80.2% | — |
| τ²-bench Banking | 26% | — |
| DeepResearch Bench | 47.8% | — |
| PostTrainBench | 22% | — |
| BALROG | 57% | — |
| ExploitBench | 26.1% | — |
| GBAEval | 0.8% | — |
| LMArena Search | 1211 | — |
| METR Time Horizons | 77% | — |
| Vending-Bench 2 | 3,774 | — |
Reasoning Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 71.7 (#12), GLM-5.3-Flash: 48.0 (#42)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| ARC-AGI-2 | 77.1% | 65.8% |
| ARC-AGI-1 | 98% | 91% |
| CritPt | 17.7% | 15.4% |
| Chess Puzzles | 55% | 14% |
| LMArena Hard Prompts | 1485 | 1491 |
| Mystery Game Puzzles | 34% | 8% |
| Epoch Capabilities Index | 154.77 | 151.88 |
| SimpleBench | 79.6% | — |
| NYT Connections (extended) | 97.4% | — |
| EnigmaEval | 36.8% | — |
| Thematic Generalization | 79.4% | — |
| EBR-Bench | 14.3% | — |
| DTBench | 97.1% | — |
| LMCA | 53.8% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 59 | — |
Math Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 62.1 (#34), GLM-5.3-Flash: 53.3 (#47)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 59.6% | 55.8% |
| FrontierMath Tier 4 | 26.8% | 17.1% |
| OTIS Mock AIME 2024-2025 | 95.6% | 93.9% |
| ProofBench | 26% | 21% |
| LMArena Math | 1485 | 1500 |
| MathArena Final-Answer Competitions | 86.5% | — |
| FrontierMath (Feb 2025 set) | 36.9% | — |
| FrontierMath Tier 4 (v1) | 16.7% | — |
Knowledge Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 71.8 (#3), GLM-5.3-Flash: 58.4 (#36)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 94.4% | 90.2% |
| LMArena Expert | 1485 | 1513 |
| Humanity's Last Exam | 46.4% | — |
| SimpleQA Verified | 73.5% | — |
| Vectara Hallucination Rate | 10.4% | — |
Multimodal GLM-5.3-Flash leads
Gemini 3.1 Pro Preview: 37.9 (#69), GLM-5.3-Flash: 42.8 (#27)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1296 | 1296 |
| Blueprint-Bench 2 | 26.5% | — |
| Furniture Assembly | 26.7% | — |
| LMArena Document | 1444 | — |
Multilingual Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 57.0 (#12), GLM-5.3-Flash: 56.0 (#25)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1477 | 1462 |
| LMArena Chinese | 1529 | 1527 |
| LMArena French | 1487 | 1496 |
| LMArena German | 1491 | 1470 |
| LMArena Japanese | 1493 | 1429 |
| LMArena Korean | 1455 | 1446 |
| LMArena Russian | 1498 | 1469 |
| LMArena Spanish | 1479 | 1471 |
Instruction Following Too close to call
Gemini 3.1 Pro Preview: 77.0 (#32), GLM-5.3-Flash: 77.5 (#20)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1466 | 1478 |
Long Context Gemini 3.1 Pro Preview leads
Gemini 3.1 Pro Preview: 47.4 (#18), GLM-5.3-Flash: 45.4 (#39)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1483 | 1482 |
| CL-bench | 20.8% | — |
| CL-bench Life | 16.9% | — |
Writing & Preference Too close to call
Gemini 3.1 Pro Preview: 66.1 (#37), GLM-5.3-Flash: 65.3 (#50)
| Benchmark | Gemini 3.1 Pro Preview | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1481 | 1471 |
| LMArena Creative Writing | 1482 | 1442 |
| LMArena Multi-Turn | 1488 | 1467 |
| EQ-Bench Creative Writing | 1491 | — |
| EQ-Bench 4 | 1142 | — |
Frequently asked questions
Is Gemini 3.1 Pro Preview better than GLM-5.3-Flash?
Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 19× less per token, which makes it the better buy when Gemini 3.1 Pro Preview's lead doesn't matter for your workload.
Which is cheaper, Gemini 3.1 Pro Preview 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; Gemini 3.1 Pro Preview lists at $2 and $12.
Is Gemini 3.1 Pro Preview or GLM-5.3-Flash better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 42.5 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.1 Pro Preview does, with 1.05M tokens against 1M.
How many benchmarks do Gemini 3.1 Pro Preview and GLM-5.3-Flash share?
35 benchmarks have published results for both models. Gemini 3.1 Pro Preview has 71 scored results on Noometry and GLM-5.3-Flash has 40.