Model comparison
Codellama 34b Instruct vs GPT-5 Pro
GPT-5 Pro is the stronger model overall, scoring 46.4 to 30.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
MetaSummary
- The widest gap is in reasoning, where GPT-5 Pro leads 38.9 to 19.6.
- Codellama 34b Instruct has downloadable open weights; the other is API-only.
Side by side
| Codellama 34b Instruct | GPT-5 Pro | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 30.8 | 46.4 |
| Released | — | 2025-10-06 |
| Weights | Open | Proprietary |
| Context window | — | 400K |
| Max output | — | 272K |
| Input $ / M tokens | — | $15 |
| Output $ / M tokens | — | $120 |
| Results tracked | 14 | 12 |
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Category by category
Coding GPT-5 Pro leads
Codellama 34b Instruct: 28.5 (#314), GPT-5 Pro: 44.0 (#80)
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| WeirdML | — | 60.4% |
| BigCodeBench Instruct | 29% | — |
| LMArena Coding | 1046 | — |
| BigCodeBench Complete | 37.1% | — |
| AlgoTune | — | 1.31 |
| HumanEval+ | 43.9% | — |
| MBPP+ | 56.3% | — |
Reasoning GPT-5 Pro leads
Codellama 34b Instruct: 19.6 (#255), GPT-5 Pro: 38.9 (#62)
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| ARC-AGI-2 | — | 18.3% |
| SimpleBench | — | 61.6% |
| Kagi LLM Benchmark | — | 76.8% |
| ARC-AGI-1 | — | 70.2% |
| EnigmaEval | — | 18.8% |
| LMArena Hard Prompts | 1032 | — |
| Epoch Capabilities Index | — | 150.28 |
Math GPT-5 Pro leads
Codellama 34b Instruct: 31.0 (#230), GPT-5 Pro: 48.5 (#63)
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 55.8% |
| FrontierMath Tier 4 | — | 19.5% |
| LMArena Math | 1056 | — |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge Not comparable
Codellama 34b Instruct: —, GPT-5 Pro: 56.7 (#42)
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| Humanity's Last Exam | — | 31.6% |
Multilingual Not comparable
Codellama 34b Instruct: 25.8 (#284), GPT-5 Pro: —
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| LMArena Non-English | 1011 | — |
| LMArena Chinese | 976 | — |
Instruction Following Not comparable
Codellama 34b Instruct: 52.2 (#291), GPT-5 Pro: —
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| LMArena Instruction Following | 1028 | — |
Long Context Not comparable
Codellama 34b Instruct: 30.9 (#284), GPT-5 Pro: —
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| LMArena Longer Query | 1013 | — |
Writing & Preference Not comparable
Codellama 34b Instruct: 28.2 (#297), GPT-5 Pro: —
| Benchmark | Codellama 34b Instruct | GPT-5 Pro |
|---|---|---|
| LMArena Text | 1066 | — |
| LMArena Creative Writing | 1032 | — |
| LMArena Multi-Turn | 1015 | — |
Frequently asked questions
Is Codellama 34b Instruct better than GPT-5 Pro?
GPT-5 Pro is the stronger model overall, scoring 46.4 to 30.8 on the Noometry Index.
Is Codellama 34b Instruct or GPT-5 Pro better for coding?
GPT-5 Pro scores higher on coding benchmarks: 44.0 versus 28.5 in the Noometry coding category.
How many benchmarks do Codellama 34b Instruct and GPT-5 Pro share?
0 benchmarks have published results for both models. Codellama 34b Instruct has 14 scored results on Noometry and GPT-5 Pro has 12.