Model comparison
Codellama 70b Instruct vs GLM-4.6
GLM-4.6 is the stronger model overall, scoring 41.4 to 33.7 on the Noometry Index.
Last verified . 4 shared benchmarks.
MetaSummary
- They share 4 benchmarks with published results for both. Codellama 70b Instruct scores higher in 0 categories and GLM-4.6 in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.6 leads 53.5 to 24.8.
Side by side
| Codellama 70b Instruct | GLM-4.6 | |
|---|---|---|
| Provider | Meta | Z.ai (Zhipu) |
| Noometry Index | 33.7 | 41.4 |
| Released | — | 2025-09-30 |
| Weights | Open | Open |
| Context window | — | 205K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $2.20 |
| Results tracked | 7 | 29 |
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Category by category
Coding GLM-4.6 leads
Codellama 70b Instruct: 37.6 (#193), GLM-4.6: 40.1 (#148)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1340 |
| SciCode | — | 38.4% |
| BigCodeBench Instruct | 40.7% | — |
| LMArena Coding | — | 1449 |
| BigCodeBench Complete | 49.6% | — |
| ALE-Bench | — | 340.82 |
| HumanEval+ | 65.9% | — |
Agentic & Tool Use Not comparable
Codellama 70b Instruct: —, GLM-4.6: 32.3 (#66)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| Terminal-Bench | — | 24.5% |
| Berkeley Function Calling Leaderboard | — | 72.4% |
Reasoning GLM-4.6 leads
Codellama 70b Instruct: 20.1 (#242), GLM-4.6: 23.7 (#172)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| LMArena Hard Prompts | 1052 | 1440 |
| Kagi LLM Benchmark | — | 47.4% |
| CritPt | — | 1.1% |
Math Not comparable
Codellama 70b Instruct: —, GLM-4.6: 39.1 (#111)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| LMArena Math | — | 1432 |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Not comparable
Codellama 70b Instruct: —, GLM-4.6: 40.2 (#124)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| Vectara Hallucination Rate | — | 9.5% |
| LMArena Expert | — | 1431 |
Multilingual GLM-4.6 leads
Codellama 70b Instruct: 24.8 (#288), GLM-4.6: 53.5 (#66)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| LMArena Non-English | 992 | 1426 |
| LMArena Chinese | — | 1499 |
| LMArena French | — | 1459 |
| LMArena German | — | 1447 |
| LMArena Japanese | — | 1393 |
| LMArena Korean | — | 1400 |
| LMArena Russian | — | 1419 |
| LMArena Spanish | — | 1436 |
Instruction Following GLM-4.6 leads
Codellama 70b Instruct: 51.9 (#293), GLM-4.6: 74.3 (#98)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | 1024 | 1410 |
Long Context Not comparable
Codellama 70b Instruct: —, GLM-4.6: 43.4 (#94)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | — | 1422 |
Writing & Preference GLM-4.6 leads
Codellama 70b Instruct: 33.4 (#277), GLM-4.6: 61.1 (#90)
| Benchmark | Codellama 70b Instruct | GLM-4.6 |
|---|---|---|
| LMArena Text | 1057 | 1440 |
| LMArena Creative Writing | — | 1411 |
| EQ-Bench Creative Writing | — | 1411 |
| LMArena Multi-Turn | — | 1427 |
Frequently asked questions
Is Codellama 70b Instruct better than GLM-4.6?
GLM-4.6 is the stronger model overall, scoring 41.4 to 33.7 on the Noometry Index.
Is Codellama 70b Instruct or GLM-4.6 better for coding?
GLM-4.6 scores higher on coding benchmarks: 40.1 versus 37.6 in the Noometry coding category.
How many benchmarks do Codellama 70b Instruct and GLM-4.6 share?
4 benchmarks have published results for both models. Codellama 70b Instruct has 7 scored results on Noometry and GLM-4.6 has 29.