# Codellama 34b Instruct vs GLM-5.3

> GLM-5.3 is the stronger model overall, scoring 54.8 to 30.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/codellama-34b-instruct-vs-glm-5-3
- Last updated: 2026-10-10
- Shared benchmarks: 10

## Summary

- They share 10 benchmarks with published results for both. Codellama 34b Instruct scores higher in 0 categories and GLM-5.3 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5.3 leads 75.7 to 28.2.

## Snapshot

| | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| Provider | Meta | Z.ai (Zhipu) |
| Noometry Index | 30.8 | 54.8 |
| Rank | 287 | 26 |
| Context | — | 1M |
| Input $/M | — | $1.40 |
| Output $/M | — | $4.40 |
| Weights | Open | Open |

## Coding

- Codellama 34b Instruct: 28.5 (#314)
- GLM-5.3: 59.5 (#14)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| LMArena Coding | 1046 | 1496 |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| CursorBench | — | 42.6% |
| LMArena WebDev | — | 1622 |
| FrontierSWE | — | 30.2% |
| SciCode | — | 59% |
| WeirdML | — | 75.4% |
| BigCodeBench Instruct | 29% | — |
| BigCodeBench Complete | 37.1% | — |
| ALE-Bench | — | 1,317 |
| HumanEval+ | 43.9% | — |
| MBPP+ | 56.3% | — |

## Agentic & Tool Use

- Codellama 34b Instruct: —
- GLM-5.3: 36.4 (#38)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| APEX-Agents | — | 56.6% |
| Vending-Bench 2 | — | 8,164 |

## Reasoning

- Codellama 34b Instruct: 19.6 (#255)
- GLM-5.3: 46.1 (#46)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| LMArena Hard Prompts | 1032 | 1489 |
| NYT Connections (extended) | — | 74.2% |
| CritPt | — | 19.1% |
| Chess Puzzles | — | 21% |
| Mystery Game Puzzles | — | 33% |
| DTBench | — | 87.7% |
| LMCA | — | 55.5% |
| Bench to the Future 3 | — | 0.15 |
| Epoch Capabilities Index | — | 155.61 |

## Math

- Codellama 34b Instruct: 31.0 (#230)
- GLM-5.3: 62.3 (#33)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| LMArena Math | 1056 | 1489 |
| FrontierMath (Tiers 1-3) | — | 68.8% |
| FrontierMath Tier 4 | — | 29.3% |
| OTIS Mock AIME 2024-2025 | — | 91.1% |
| ProofBench | — | 49% |

## Knowledge

- Codellama 34b Instruct: —
- GLM-5.3: 58.3 (#37)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 41% |
| LMArena Expert | — | 1516 |

## Multilingual

- Codellama 34b Instruct: 25.8 (#284)
- GLM-5.3: 55.7 (#28)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1011 | 1457 |
| LMArena Chinese | 976 | 1528 |
| LMArena French | — | 1499 |
| LMArena German | — | 1499 |
| LMArena Japanese | — | 1453 |
| LMArena Korean | — | 1472 |
| LMArena Russian | — | 1463 |
| LMArena Spanish | — | 1460 |

## Instruction Following

- Codellama 34b Instruct: 52.2 (#291)
- GLM-5.3: 77.5 (#23)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1028 | 1477 |

## Long Context

- Codellama 34b Instruct: 30.9 (#284)
- GLM-5.3: 45.4 (#41)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1013 | 1482 |

## Writing & Preference

- Codellama 34b Instruct: 28.2 (#297)
- GLM-5.3: 75.7 (#6)

| Benchmark | Codellama 34b Instruct | GLM-5.3 |
|---|---|---|
| LMArena Text | 1066 | 1471 |
| LMArena Creative Writing | 1032 | 1457 |
| LMArena Multi-Turn | 1015 | 1472 |
| EQ-Bench Creative Writing | — | 2075 |

## FAQ

### Is Codellama 34b Instruct better than GLM-5.3?

GLM-5.3 is the stronger model overall, scoring 54.8 to 30.8 on the Noometry Index.

### Is Codellama 34b Instruct or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 28.5 in the Noometry coding category.

### How many benchmarks do Codellama 34b Instruct and GLM-5.3 share?

10 benchmarks have published results for both models. Codellama 34b Instruct has 14 scored results on Noometry and GLM-5.3 has 42.