Model comparison
Codellama 34b Instruct vs Qwen2.5 72B Instruct
Qwen2.5 72B Instruct is the stronger model overall, scoring 31.9 to 30.8 on the Noometry Index.
Last verified . 12 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. Codellama 34b Instruct scores higher in 1 category and Qwen2.5 72B Instruct in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen2.5 72B Instruct leads 46.7 to 28.2.
- The biggest single-benchmark swing is BigCodeBench Complete: 37.1% for Codellama 34b Instruct and 55.9% for Qwen2.5 72B Instruct.
Side by side
| Codellama 34b Instruct | Qwen2.5 72B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.8 | 31.9 |
| Released | — | 2024-09 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $1.40 |
| Output $ / M tokens | — | $5.60 |
| Results tracked | 14 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Qwen2.5 72B Instruct leads
Codellama 34b Instruct: 28.5 (#314), Qwen2.5 72B Instruct: 33.2 (#260)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| BigCodeBench Instruct | 29% | 45.8% |
| LMArena Coding | 1046 | 1292 |
| BigCodeBench Complete | 37.1% | 55.9% |
| WeirdML | — | 16% |
| HumanEval+ | 43.9% | — |
| MBPP+ | 56.3% | — |
Agentic & Tool Use Not comparable
Codellama 34b Instruct: —, Qwen2.5 72B Instruct: 22.1 (#133)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| TheAgentCompany | — | 5.7% |
| BALROG | — | 16.2% |
| METR Time Horizons | — | 35.8% |
Reasoning Qwen2.5 72B Instruct leads
Codellama 34b Instruct: 19.6 (#255), Qwen2.5 72B Instruct: 22.3 (#199)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1032 | 1271 |
| DTBench | — | 62.9% |
| LMCA | — | 13.4% |
| BIG-Bench Hard | — | 79.8% |
| Epoch Capabilities Index | — | 129 |
| ForecastBench | — | 57.5 |
| HellaSwag | — | 84.8% |
| PIQA | — | 82.6% |
| WinoGrande | — | 82.3% |
Math Codellama 34b Instruct leads
Codellama 34b Instruct: 31.0 (#230), Qwen2.5 72B Instruct: 19.3 (#287)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Math | 1056 | 1283 |
| OTIS Mock AIME 2024-2025 | — | 8.1% |
| Omni-MATH | — | 33% |
| MATH Level 5 | — | 63.2% |
Knowledge Not comparable
Codellama 34b Instruct: —, Qwen2.5 72B Instruct: 27.0 (#253)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| GPQA Diamond | — | 49.1% |
| MMLU-Pro | — | 63.1% |
| Confabulations | — | 19.1% |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1245 |
| ARC (AI2) Challenge | — | 94.5% |
| MMLU | — | 85.3% |
| TriviaQA | — | 71.9% |
Multilingual Qwen2.5 72B Instruct leads
Codellama 34b Instruct: 25.8 (#284), Qwen2.5 72B Instruct: 41.0 (#213)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Non-English | 1011 | 1252 |
| LMArena Chinese | 976 | 1272 |
| LMArena French | — | 1280 |
| LMArena German | — | 1234 |
| LMArena Japanese | — | 1180 |
| LMArena Korean | — | 1188 |
| LMArena Russian | — | 1264 |
| LMArena Spanish | — | 1256 |
Instruction Following Qwen2.5 72B Instruct leads
Codellama 34b Instruct: 52.2 (#291), Qwen2.5 72B Instruct: 65.5 (#221)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1028 | 1254 |
| IFEval | — | 80.6% |
Long Context Qwen2.5 72B Instruct leads
Codellama 34b Instruct: 30.9 (#284), Qwen2.5 72B Instruct: 38.9 (#188)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1013 | 1282 |
Writing & Preference Qwen2.5 72B Instruct leads
Codellama 34b Instruct: 28.2 (#297), Qwen2.5 72B Instruct: 46.7 (#215)
| Benchmark | Codellama 34b Instruct | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Text | 1066 | 1269 |
| LMArena Creative Writing | 1032 | 1221 |
| LMArena Multi-Turn | 1015 | 1272 |
| WildBench | — | 80.2% |
Frequently asked questions
Is Codellama 34b Instruct better than Qwen2.5 72B Instruct?
Qwen2.5 72B Instruct is the stronger model overall, scoring 31.9 to 30.8 on the Noometry Index.
Is Codellama 34b Instruct or Qwen2.5 72B Instruct better for coding?
Qwen2.5 72B Instruct scores higher on coding benchmarks: 33.2 versus 28.5 in the Noometry coding category.
How many benchmarks do Codellama 34b Instruct and Qwen2.5 72B Instruct share?
12 benchmarks have published results for both models. Codellama 34b Instruct has 14 scored results on Noometry and Qwen2.5 72B Instruct has 43.