# GLM-5 vs OLMo 2 Furious 13B

> GLM-5 is the stronger model overall, scoring 45.9 to 29.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-vs-olmo-2-furious-13b
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in knowledge, where GLM-5 leads 52.2 to 18.0.

## Snapshot

| | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 45.9 | 29.2 |
| Rank | 59 | 301 |
| Context | 205K | — |
| Input $/M | $1 | — |
| Output $/M | $3.20 | — |
| Weights | Open | Open |

## Coding

- GLM-5: 49.0 (#47)
- OLMo 2 Furious 13B: 28.1 (#309)

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1461 | — |
| ALE-Bench | 765.62 | — |

## Agentic & Tool Use

- GLM-5: 30.9 (#65)
- OLMo 2 Furious 13B: —

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| 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

- GLM-5: 27.6 (#100)
- OLMo 2 Furious 13B: 14.8 (#312)

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| 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 | — | 16.3% |
| LMArena Hard Prompts | 1451 | — |
| LiveBench Data Analysis | — | 20.6% |
| Epoch Capabilities Index | 145.84 | — |
| ForecastBench | 61 | — |
| LiveBench | — | 22.1% |

## Math

- GLM-5: 44.8 (#66)
- OLMo 2 Furious 13B: 21.3 (#270)

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| Omni-MATH | — | 15.6% |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1440 | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-5: 52.2 (#59)
- OLMo 2 Furious 13B: 18.0 (#278)

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| GPQA Diamond | 87.8% | — |
| MMLU-Pro | — | 31% |
| Vectara Hallucination Rate | 10.1% | — |
| GPQA (HELM) | — | 31.6% |
| LMArena Expert | 1454 | — |

## Multilingual

- GLM-5: 53.9 (#57)
- OLMo 2 Furious 13B: —

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1430 | — |
| LMArena Chinese | 1511 | — |
| LMArena French | 1455 | — |
| LMArena German | 1445 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1421 | — |
| LMArena Russian | 1436 | — |
| LMArena Spanish | 1452 | — |

## Instruction Following

- GLM-5: 75.4 (#64)
- OLMo 2 Furious 13B: 61.1 (#243)

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | — | 60.6% |
| IFEval | — | 73% |
| LMArena Instruction Following | 1427 | — |

## Long Context

- GLM-5: 44.6 (#58)
- OLMo 2 Furious 13B: —

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| CL-bench | 18.7% | — |
| LMArena Longer Query | 1446 | — |

## Writing & Preference

- GLM-5: 66.2 (#38)
- OLMo 2 Furious 13B: 43.0 (#226)

| Benchmark | GLM-5 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Text | 1446 | — |
| LMArena Creative Writing | 1438 | — |
| EQ-Bench Creative Writing | 1601 | — |
| WildBench | — | 68.9% |
| LMArena Multi-Turn | 1456 | — |
| LiveBench Language | — | 11.2% |

## FAQ

### Is GLM-5 better than OLMo 2 Furious 13B?

GLM-5 is the stronger model overall, scoring 45.9 to 29.2 on the Noometry Index.

### Is GLM-5 or OLMo 2 Furious 13B better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 28.1 in the Noometry coding category.

### How many benchmarks do GLM-5 and OLMo 2 Furious 13B share?

0 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and OLMo 2 Furious 13B has 12.