Model comparison
Codellama 34b Instruct vs GPT-5 Nano
GPT-5 Nano is the stronger model overall, scoring 33.5 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 2 categories and GPT-5 Nano in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where GPT-5 Nano leads 75.0 to 52.2.
- Codellama 34b Instruct has downloadable open weights; the other is API-only.
Side by side
| Codellama 34b Instruct | GPT-5 Nano | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 30.8 | 33.5 |
| Released | — | 2025-08-07 |
| Weights | Open | Proprietary |
| Context window | — | 400K |
| Max output | — | 128K |
| Input $ / M tokens | — | $0.05 |
| Output $ / M tokens | — | $0.40 |
| Results tracked | 14 | 49 |
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Category by category
Coding GPT-5 Nano leads
Codellama 34b Instruct: 28.5 (#314), GPT-5 Nano: 33.6 (#254)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Coding | 1046 | 1351 |
| SWE-bench Verified (bash only) | — | 34.8% |
| WeirdML | — | 38.1% |
| BigCodeBench Instruct | 29% | — |
| BigCodeBench Complete | 37.1% | — |
| ALE-Bench | — | 718.67 |
| HumanEval+ | 43.9% | — |
| MBPP+ | 56.3% | — |
Agentic & Tool Use Not comparable
Codellama 34b Instruct: —, GPT-5 Nano: 25.8 (#106)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| Terminal-Bench | — | 21.8% |
| Berkeley Function Calling Leaderboard | — | 51.5% |
Reasoning Codellama 34b Instruct leads
Codellama 34b Instruct: 19.6 (#255), GPT-5 Nano: 16.3 (#306)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Hard Prompts | 1032 | 1328 |
| ARC-AGI-2 | — | 2.6% |
| Kagi LLM Benchmark | — | 62.2% |
| ARC-AGI-1 | — | 20.7% |
| Chess Puzzles | — | 27% |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 62.7% |
| LMCA | — | 7.9% |
| Epoch Capabilities Index | — | 139.38 |
| ForecastBench | — | 59.1 |
Math Codellama 34b Instruct leads
Codellama 34b Instruct: 31.0 (#230), GPT-5 Nano: 29.4 (#241)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Math | 1056 | 1317 |
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| OTIS Mock AIME 2024-2025 | — | 81.1% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Not comparable
Codellama 34b Instruct: —, GPT-5 Nano: 35.9 (#178)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| GPQA Diamond | — | 69.4% |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| Vectara Hallucination Rate | — | 10.5% |
| GPQA (HELM) | — | 67.9% |
| LMArena Expert | — | 1321 |
Multimodal Not comparable
Codellama 34b Instruct: —, GPT-5 Nano: 31.3 (#108)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |
Multilingual GPT-5 Nano leads
Codellama 34b Instruct: 25.8 (#284), GPT-5 Nano: 45.3 (#172)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | 1011 | 1313 |
| LMArena Chinese | 976 | 1356 |
| LMArena German | — | 1327 |
| LMArena Japanese | — | 1226 |
| LMArena Korean | — | 1269 |
| LMArena Russian | — | 1296 |
| LMArena Spanish | — | 1360 |
Instruction Following GPT-5 Nano leads
Codellama 34b Instruct: 52.2 (#291), GPT-5 Nano: 75.0 (#79)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Instruction Following | 1028 | 1306 |
| IFEval | — | 93.2% |
Long Context Too close to call
Codellama 34b Instruct: 30.9 (#284), GPT-5 Nano: 31.3 (#281)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Longer Query | 1013 | 1312 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference GPT-5 Nano leads
Codellama 34b Instruct: 28.2 (#297), GPT-5 Nano: 39.1 (#249)
| Benchmark | Codellama 34b Instruct | GPT-5 Nano |
|---|---|---|
| LMArena Text | 1066 | 1320 |
| LMArena Creative Writing | 1032 | 1249 |
| LMArena Multi-Turn | 1015 | 1311 |
| EQ-Bench Creative Writing | — | 705 |
| WildBench | — | 80.6% |
Frequently asked questions
Is Codellama 34b Instruct better than GPT-5 Nano?
GPT-5 Nano is the stronger model overall, scoring 33.5 to 30.8 on the Noometry Index.
Is Codellama 34b Instruct or GPT-5 Nano better for coding?
GPT-5 Nano scores higher on coding benchmarks: 33.6 versus 28.5 in the Noometry coding category.
How many benchmarks do Codellama 34b Instruct and GPT-5 Nano share?
10 benchmarks have published results for both models. Codellama 34b Instruct has 14 scored results on Noometry and GPT-5 Nano has 49.