Model comparison
Gemini 3.8 Flash vs GLM-5V-Turbo
Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 43.8 on the Noometry Index.
Last verified . 18 shared benchmarks.
GoogleSummary
- They share 18 benchmarks with published results for both. Gemini 3.8 Flash scores higher in 8 categories and GLM-5V-Turbo in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.8 Flash leads 76.9 to 29.7.
- Gemini 3.8 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
- Gemini 3.8 Flash accepts more context: 1.05M tokens versus 200K.
Side by side
| Gemini 3.8 Flash | GLM-5V-Turbo | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 61.8 | 43.8 |
| Released | 2026-09-02 | 2026-04-01 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 66K | 131K |
| Input $ / M tokens | $0.75 | $1.20 |
| Output $ / M tokens | $3.75 | $4 |
| Results tracked | 50 | 19 |
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Category by category
Coding Gemini 3.8 Flash leads
Gemini 3.8 Flash: 59.2 (#15), GLM-5V-Turbo: 42.1 (#111)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena WebDev | 1584 | 1401 |
| LMArena Coding | 1510 | 1466 |
| DeepSWE | 73.8% | — |
| FrontierCode | 41.2% | — |
| CursorBench | 39.6% | — |
| FrontierSWE | 19.6% | — |
| SciCode | 56.6% | — |
| WeirdML | 84.8% | — |
| ALE-Bench | 1,270 | — |
Agentic & Tool Use Not comparable
Gemini 3.8 Flash: 41.8 (#21), GLM-5V-Turbo: —
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| APEX-Agents | 64.3% | — |
| Remote Labor Index | 5.8% | — |
| GDP.pdf | 23.4% | — |
| Vending-Bench 2 | 5,094 | — |
Reasoning Gemini 3.8 Flash leads
Gemini 3.8 Flash: 76.9 (#5), GLM-5V-Turbo: 29.7 (#89)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Hard Prompts | 1508 | 1443 |
| ARC-AGI-2 | 89.2% | — |
| NYT Connections (extended) | 97.4% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 18.3% | — |
| Chess Puzzles | 61% | — |
| Mystery Game Puzzles | 47% | — |
| DTBench | 95.7% | — |
| LMCA | 52.9% | — |
| Surface Evolver Bench | 76.9% | — |
| Epoch Capabilities Index | 156.71 | — |
Math Gemini 3.8 Flash leads
Gemini 3.8 Flash: 65.3 (#28), GLM-5V-Turbo: 39.4 (#106)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Math | 1528 | 1441 |
| FrontierMath (Tiers 1-3) | 68.4% | — |
| FrontierMath Tier 4 | 22% | — |
| OTIS Mock AIME 2024-2025 | 98.9% | — |
| ProofBench | 48% | — |
Knowledge Gemini 3.8 Flash leads
Gemini 3.8 Flash: 74.8 (#2), GLM-5V-Turbo: 40.6 (#117)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Expert | 1524 | 1452 |
| GPQA Diamond | 95.4% | — |
| Humanity's Last Exam | 44.5% | — |
| SimpleQA Verified | 69.7% | — |
Multimodal Too close to call
Gemini 3.8 Flash: 40.7 (#45), GLM-5V-Turbo: 40.9 (#42)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Vision | 1314 | 1264 |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 31.7% | — |
| LMArena Document | — | 1416 |
Multilingual Gemini 3.8 Flash leads
Gemini 3.8 Flash: 58.0 (#5), GLM-5V-Turbo: 53.0 (#73)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Non-English | 1491 | 1420 |
| LMArena Chinese | 1554 | 1488 |
| LMArena French | 1498 | 1444 |
| LMArena German | 1493 | 1423 |
| LMArena Korean | 1459 | 1396 |
| LMArena Russian | 1515 | 1431 |
| LMArena Spanish | 1485 | 1450 |
| LMArena Japanese | 1502 | — |
Instruction Following Gemini 3.8 Flash leads
Gemini 3.8 Flash: 78.0 (#13), GLM-5V-Turbo: 75.0 (#80)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Instruction Following | 1490 | 1423 |
Long Context Gemini 3.8 Flash leads
Gemini 3.8 Flash: 46.3 (#24), GLM-5V-Turbo: 44.0 (#80)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Longer Query | 1508 | 1438 |
Writing & Preference Gemini 3.8 Flash leads
Gemini 3.8 Flash: 72.2 (#15), GLM-5V-Turbo: 62.5 (#73)
| Benchmark | Gemini 3.8 Flash | GLM-5V-Turbo |
|---|---|---|
| LMArena Text | 1499 | 1437 |
| LMArena Creative Writing | 1492 | 1416 |
| LMArena Multi-Turn | 1501 | 1432 |
| EQ-Bench Creative Writing | 1748 | — |
Frequently asked questions
Is Gemini 3.8 Flash better than GLM-5V-Turbo?
Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 43.8 on the Noometry Index.
Which is cheaper, Gemini 3.8 Flash or GLM-5V-Turbo?
Gemini 3.8 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.
Is Gemini 3.8 Flash or GLM-5V-Turbo better for coding?
Gemini 3.8 Flash scores higher on coding benchmarks: 59.2 versus 42.1 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.8 Flash does, with 1.05M tokens against 200K.
How many benchmarks do Gemini 3.8 Flash and GLM-5V-Turbo share?
18 benchmarks have published results for both models. Gemini 3.8 Flash has 50 scored results on Noometry and GLM-5V-Turbo has 19.