Model comparison
Gemini 3.6 Flash vs GLM-5
Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 46.1 on the Noometry Index.
Last verified . 29 shared benchmarks.
GoogleSummary
- They share 29 benchmarks with published results for both. Gemini 3.6 Flash scores higher in 9 categories and GLM-5 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.6 Flash leads 58.8 to 27.6.
- The biggest single-benchmark swing is ARC-AGI-2: 60.4% for Gemini 3.6 Flash and 4.9% for GLM-5.
- Both cost about the same: $0.75 input and $3.75 output per million tokens.
- Gemini 3.6 Flash accepts more context: 1.05M tokens versus 205K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| Gemini 3.6 Flash | GLM-5 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | |
| Noometry Index | 54.1 | 46.1 |
| Released | 2026-07-21 | 2026-02-11 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 205K |
| Max output | 66K | 131K |
| Input $ / M tokens | $0.75 | $1 |
| Output $ / M tokens | $3.75 | $3.20 |
| Results tracked | 46 | 45 |
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Category by category
Coding Gemini 3.6 Flash leads
Gemini 3.6 Flash: 50.0 (#48), GLM-5: 49.0 (#52)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| LMArena WebDev | 1538 | 1434 |
| WeirdML | 56.1% | 48.2% |
| LMArena Coding | 1491 | 1461 |
| ALE-Bench | 715.52 | 765.62 |
| SWE-bench Verified | — | 72.1% |
| DeepSWE | 46.7% | — |
| FrontierCode | 34.4% | — |
| SWE-bench Verified (bash only) | — | 72.8% |
| SWE-bench Multilingual | — | 69.7% |
| SciCode | 52.7% | — |
Agentic & Tool Use Gemini 3.6 Flash leads
Gemini 3.6 Flash: 32.3 (#65), GLM-5: 31.1 (#71)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| Terminal-Bench | — | 52.4% |
| APEX-Agents | 46.9% | — |
| τ²-bench Airline | — | 82.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 73.7% |
| τ²-bench Telecom | — | 86.8% |
| GDP.pdf | 14% | — |
| Vending-Bench 2 | — | 4,432 |
Reasoning Gemini 3.6 Flash leads
Gemini 3.6 Flash: 58.8 (#22), GLM-5: 27.6 (#116)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| ARC-AGI-2 | 60.4% | 4.9% |
| NYT Connections (extended) | 89% | 74.8% |
| ARC-AGI-1 | 91.2% | 44.7% |
| Chess Puzzles | 43% | 10% |
| LMArena Hard Prompts | 1485 | 1452 |
| Epoch Capabilities Index | 154.25 | 145.83 |
| SimpleBench | — | 53.2% |
| Kagi LLM Benchmark | — | 75% |
| CritPt | 10.6% | — |
| Mystery Game Puzzles | 30% | — |
| DTBench | 95.5% | — |
| LMCA | 44.9% | — |
| ForecastBench | — | 61 |
Math Gemini 3.6 Flash leads
Gemini 3.6 Flash: 57.3 (#40), GLM-5: 46.4 (#71)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| MathArena Final-Answer Competitions | 70.8% | 65.7% |
| OTIS Mock AIME 2024-2025 | 94.2% | 80% |
| LMArena Math | 1505 | 1440 |
| FrontierMath (Tiers 1-3) | 58.9% | — |
| FrontierMath Tier 4 | 22% | — |
| ProofBench | 36% | — |
| FrontierMath (Feb 2025 set) | — | 16.4% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Gemini 3.6 Flash leads
Gemini 3.6 Flash: 67.8 (#8), GLM-5: 52.3 (#64)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| GPQA Diamond | 94.1% | 87.8% |
| LMArena Expert | 1488 | 1454 |
| SimpleQA Verified | 66.2% | — |
| Vectara Hallucination Rate | — | 10.1% |
Multimodal Not comparable
Gemini 3.6 Flash: 38.5 (#64), GLM-5: —
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| LMArena Vision | 1298 | — |
| Blueprint-Bench 2 | 31.2% | — |
| Furniture Assembly | 23.3% | — |
| LMArena Document | 1456 | — |
Multilingual Gemini 3.6 Flash leads
Gemini 3.6 Flash: 56.5 (#19), GLM-5: 53.7 (#58)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| LMArena Non-English | 1469 | 1430 |
| LMArena Chinese | 1531 | 1511 |
| LMArena French | 1504 | 1455 |
| LMArena German | 1478 | 1445 |
| LMArena Japanese | 1476 | 1416 |
| LMArena Korean | 1431 | 1423 |
| LMArena Russian | 1487 | 1436 |
| LMArena Spanish | 1475 | 1454 |
Instruction Following Gemini 3.6 Flash leads
Gemini 3.6 Flash: 77.0 (#33), GLM-5: 75.2 (#67)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| LMArena Instruction Following | 1466 | 1428 |
Long Context Too close to call
Gemini 3.6 Flash: 45.1 (#50), GLM-5: 44.7 (#60)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| LMArena Longer Query | 1474 | 1446 |
| CL-bench | — | 18.7% |
Writing & Preference Gemini 3.6 Flash leads
Gemini 3.6 Flash: 68.2 (#27), GLM-5: 66.0 (#38)
| Benchmark | Gemini 3.6 Flash | GLM-5 |
|---|---|---|
| LMArena Text | 1479 | 1446 |
| LMArena Creative Writing | 1465 | 1439 |
| EQ-Bench Creative Writing | 1604 | 1601 |
| LMArena Multi-Turn | 1481 | 1456 |
Frequently asked questions
Is Gemini 3.6 Flash better than GLM-5?
Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 46.1 on the Noometry Index.
Which is cheaper, Gemini 3.6 Flash or GLM-5?
Gemini 3.6 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GLM-5 lists at $1 and $3.20.
Is Gemini 3.6 Flash or GLM-5 better for coding?
Gemini 3.6 Flash scores higher on coding benchmarks: 50.0 versus 49.0 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.6 Flash does, with 1.05M tokens against 205K.
How many benchmarks do Gemini 3.6 Flash and GLM-5 share?
29 benchmarks have published results for both models. Gemini 3.6 Flash has 46 scored results on Noometry and GLM-5 has 45.