Model comparison
Codellama 34b Instruct vs GLM-4.7-Flash
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.8 on the Noometry Index.
Last verified . 10 shared benchmarks.
MetaSummary
- They share 10 benchmarks with published results for both. Codellama 34b Instruct scores higher in 0 categories and GLM-4.7-Flash in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.7-Flash leads 46.5 to 25.8.
Side by side
| Codellama 34b Instruct | GLM-4.7-Flash | |
|---|---|---|
| Provider | Meta | Z.ai (Zhipu) |
| Noometry Index | 30.8 | 38.8 |
| Released | — | 2026-01-19 |
| Weights | Open | Open |
| Context window | — | 200K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.06 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 14 | 21 |
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Category by category
Coding GLM-4.7-Flash leads
Codellama 34b Instruct: 28.5 (#314), GLM-4.7-Flash: 40.6 (#135)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1046 | 1383 |
| BigCodeBench Instruct | 29% | — |
| BigCodeBench Complete | 37.1% | — |
| HumanEval+ | 43.9% | — |
| MBPP+ | 56.3% | — |
Reasoning GLM-4.7-Flash leads
Codellama 34b Instruct: 19.6 (#255), GLM-4.7-Flash: 20.9 (#229)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| LMArena Hard Prompts | 1032 | 1356 |
| Chess Puzzles | — | 0% |
Math GLM-4.7-Flash leads
Codellama 34b Instruct: 31.0 (#230), GLM-4.7-Flash: 36.1 (#173)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| LMArena Math | 1056 | 1355 |
| OTIS Mock AIME 2024-2025 | — | 58.3% |
Knowledge Not comparable
Codellama 34b Instruct: —, GLM-4.7-Flash: 35.5 (#184)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| GPQA Diamond | — | 60.5% |
| Vectara Hallucination Rate | — | 9.3% |
| LMArena Expert | — | 1357 |
Multilingual GLM-4.7-Flash leads
Codellama 34b Instruct: 25.8 (#284), GLM-4.7-Flash: 46.5 (#158)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1011 | 1330 |
| LMArena Chinese | 976 | 1403 |
| LMArena French | — | 1332 |
| LMArena German | — | 1337 |
| LMArena Korean | — | 1283 |
| LMArena Russian | — | 1332 |
| LMArena Spanish | — | 1350 |
Instruction Following GLM-4.7-Flash leads
Codellama 34b Instruct: 52.2 (#291), GLM-4.7-Flash: 70.1 (#167)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1028 | 1327 |
Long Context GLM-4.7-Flash leads
Codellama 34b Instruct: 30.9 (#284), GLM-4.7-Flash: 40.9 (#148)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1013 | 1345 |
Writing & Preference GLM-4.7-Flash leads
Codellama 34b Instruct: 28.2 (#297), GLM-4.7-Flash: 47.4 (#210)
| Benchmark | Codellama 34b Instruct | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1066 | 1351 |
| LMArena Creative Writing | 1032 | 1297 |
| LMArena Multi-Turn | 1015 | 1342 |
| EQ-Bench Creative Writing | — | 1125 |
Frequently asked questions
Is Codellama 34b Instruct better than GLM-4.7-Flash?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.8 on the Noometry Index.
Is Codellama 34b Instruct or GLM-4.7-Flash better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 28.5 in the Noometry coding category.
How many benchmarks do Codellama 34b Instruct and GLM-4.7-Flash share?
10 benchmarks have published results for both models. Codellama 34b Instruct has 14 scored results on Noometry and GLM-4.7-Flash has 21.