# Gemma 2 27B vs GLM-5

> GLM-5 is the stronger model overall, scoring 46.1 to 29.4 on the Noometry Index. Gemma 2 27B costs 2.4× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemma-2-27b-vs-glm-5
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. Gemma 2 27B scores higher in 0 categories and GLM-5 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5 leads 46.4 to 10.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.4% for Gemma 2 27B and 80% for GLM-5.
- Gemma 2 27B is cheaper at $0.65 / $0.65 per million input/output tokens, against $1 / $3.20 for GLM-5.
- GLM-5 accepts more context: 205K tokens versus 8K.

## Snapshot

| | Gemma 2 27B | GLM-5 |
|---|---|---|
| Provider | Google | Z.ai (Zhipu) |
| Noometry Index | 29.4 | 46.1 |
| Rank | 312 | 66 |
| Context | 8K | 205K |
| Input $/M | $0.65 | $1 |
| Output $/M | $0.65 | $3.20 |
| Weights | Open | Open |

## Coding

- Gemma 2 27B: 34.1 (#246)
- GLM-5: 49.0 (#52)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| LMArena Coding | 1211 | 1461 |
| SWE-bench Verified | — | 72.1% |
| SWE-bench Verified (bash only) | — | 72.8% |
| LMArena WebDev | — | 1434 |
| SWE-bench Multilingual | — | 69.7% |
| WeirdML | — | 48.2% |
| BigCodeBench Instruct | 42.8% | — |
| LiveBench Coding | 36% | — |
| BigCodeBench Complete | 52.5% | — |
| ALE-Bench | — | 765.62 |

## Agentic & Tool Use

- Gemma 2 27B: —
- GLM-5: 31.1 (#71)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| Terminal-Bench | — | 52.4% |
| τ²-bench Airline | — | 82.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 73.7% |
| τ²-bench Telecom | — | 86.8% |
| Vending-Bench 2 | — | 4,432 |

## Reasoning

- Gemma 2 27B: 15.3 (#315)
- GLM-5: 27.6 (#116)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| LMArena Hard Prompts | 1198 | 1452 |
| Epoch Capabilities Index | 122.08 | 145.83 |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | — | 53.2% |
| Kagi LLM Benchmark | — | 75% |
| NYT Connections (extended) | — | 74.8% |
| ARC-AGI-1 | — | 44.7% |
| Chess Puzzles | — | 10% |
| LiveBench Reasoning | 28.1% | — |
| DTBench | 48% | — |
| LiveBench Data Analysis | 47.9% | — |
| LMCA | 7.1% | — |
| ForecastBench | — | 61 |
| LiveBench | 38.2% | — |

## Math

- Gemma 2 27B: 10.7 (#311)
- GLM-5: 46.4 (#71)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.4% | 80% |
| LMArena Math | 1212 | 1440 |
| MathArena Final-Answer Competitions | — | 65.7% |
| LiveBench Math | 26.5% | — |
| MATH Level 5 | 27.9% | — |
| FrontierMath (Feb 2025 set) | — | 16.4% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- Gemma 2 27B: 19.0 (#280)
- GLM-5: 52.3 (#64)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| GPQA Diamond | 36.5% | 87.8% |
| LMArena Expert | 1172 | 1454 |
| Confabulations | 27.1% | — |
| Vectara Hallucination Rate | — | 10.1% |
| MMLU | 75.7% | — |

## Multilingual

- Gemma 2 27B: 38.6 (#226)
- GLM-5: 53.7 (#58)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| LMArena Non-English | 1217 | 1430 |
| LMArena Chinese | 1221 | 1511 |
| LMArena French | 1247 | 1455 |
| LMArena German | 1209 | 1445 |
| LMArena Japanese | 1175 | 1416 |
| LMArena Korean | 1174 | 1423 |
| LMArena Russian | 1234 | 1436 |
| LMArena Spanish | 1228 | 1454 |

## Instruction Following

- Gemma 2 27B: 60.5 (#249)
- GLM-5: 75.2 (#67)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| LMArena Instruction Following | 1206 | 1428 |
| LiveBench Instruction Following | 58.1% | — |

## Long Context

- Gemma 2 27B: 37.3 (#218)
- GLM-5: 44.7 (#60)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| LMArena Longer Query | 1231 | 1446 |
| CL-bench | — | 18.7% |

## Writing & Preference

- Gemma 2 27B: 44.2 (#225)
- GLM-5: 66.0 (#38)

| Benchmark | Gemma 2 27B | GLM-5 |
|---|---|---|
| LMArena Text | 1231 | 1446 |
| LMArena Creative Writing | 1241 | 1439 |
| LMArena Multi-Turn | 1224 | 1456 |
| EQ-Bench Creative Writing | — | 1601 |
| LiveBench Language | 32.6% | — |

## FAQ

### Is Gemma 2 27B better than GLM-5?

GLM-5 is the stronger model overall, scoring 46.1 to 29.4 on the Noometry Index. Gemma 2 27B costs 2.4× less per token, which makes it the better buy when GLM-5's lead doesn't matter for your workload.

### Which is cheaper, Gemma 2 27B or GLM-5?

Gemma 2 27B is cheaper. It lists at $0.65 per million input tokens and $0.65 per million output tokens; GLM-5 lists at $1 and $3.20.

### Is Gemma 2 27B or GLM-5 better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 34.1 in the Noometry coding category.

### Which has the bigger context window?

GLM-5 does, with 205K tokens against 8K.

### How many benchmarks do Gemma 2 27B and GLM-5 share?

20 benchmarks have published results for both models. Gemma 2 27B has 34 scored results on Noometry and GLM-5 has 45.