Model comparison
Codellama 34b Instruct vs Llama 4 Scout
Codellama 34b Instruct is the stronger model overall, scoring 30.8 to 27.7 on the Noometry Index.
Last verified . 11 shared benchmarks.
MetaSummary
- They share 11 benchmarks with published results for both. Codellama 34b Instruct scores higher in 4 categories and Llama 4 Scout in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Llama 4 Scout leads 41.0 to 25.8.
- The biggest single-benchmark swing is BigCodeBench Complete: 37.1% for Codellama 34b Instruct and 43.1% for Llama 4 Scout.
Side by side
| Codellama 34b Instruct | Llama 4 Scout | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 30.8 | 27.7 |
| Released | — | 2025-04-05 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.30 |
| Results tracked | 14 | 43 |
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Category by category
Coding Codellama 34b Instruct leads
Codellama 34b Instruct: 28.5 (#314), Llama 4 Scout: 20.2 (#339)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Coding | 1046 | 1286 |
| BigCodeBench Complete | 37.1% | 43.1% |
| SWE-bench Verified (bash only) | — | 9.1% |
| SciCode | — | 17% |
| BigCodeBench Instruct | 29% | — |
| HumanEval+ | 43.9% | — |
| MBPP+ | 56.3% | — |
Agentic & Tool Use Not comparable
Codellama 34b Instruct: —, Llama 4 Scout: 24.6 (#119)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Codellama 34b Instruct leads
Codellama 34b Instruct: 19.6 (#255), Llama 4 Scout: 9.1 (#345)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Hard Prompts | 1032 | 1266 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| Epoch Capabilities Index | — | 129.64 |
| ForecastBench | — | 57.5 |
Math Codellama 34b Instruct leads
Codellama 34b Instruct: 31.0 (#230), Llama 4 Scout: 19.6 (#286)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Math | 1056 | 1287 |
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge Not comparable
Codellama 34b Instruct: —, Llama 4 Scout: 31.9 (#217)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
| LMArena Expert | — | 1235 |
Multimodal Not comparable
Codellama 34b Instruct: —, Llama 4 Scout: 32.2 (#102)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Llama 4 Scout leads
Codellama 34b Instruct: 25.8 (#284), Llama 4 Scout: 41.0 (#212)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | 1011 | 1252 |
| LMArena Chinese | 976 | 1255 |
| LMArena French | — | 1282 |
| LMArena German | — | 1272 |
| LMArena Japanese | — | 1206 |
| LMArena Korean | — | 1207 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1278 |
Instruction Following Llama 4 Scout leads
Codellama 34b Instruct: 52.2 (#291), Llama 4 Scout: 65.8 (#217)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Instruction Following | 1028 | 1248 |
| IFEval | — | 81.8% |
Long Context Codellama 34b Instruct leads
Codellama 34b Instruct: 30.9 (#284), Llama 4 Scout: 27.5 (#294)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Longer Query | 1013 | 1265 |
| Fiction.LiveBench | — | 36% |
Writing & Preference Llama 4 Scout leads
Codellama 34b Instruct: 28.2 (#297), Llama 4 Scout: 37.0 (#261)
| Benchmark | Codellama 34b Instruct | Llama 4 Scout |
|---|---|---|
| LMArena Text | 1066 | 1279 |
| LMArena Creative Writing | 1032 | 1249 |
| LMArena Multi-Turn | 1015 | 1280 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
Frequently asked questions
Is Codellama 34b Instruct better than Llama 4 Scout?
Codellama 34b Instruct is the stronger model overall, scoring 30.8 to 27.7 on the Noometry Index.
Is Codellama 34b Instruct or Llama 4 Scout better for coding?
Codellama 34b Instruct scores higher on coding benchmarks: 28.5 versus 20.2 in the Noometry coding category.
How many benchmarks do Codellama 34b Instruct and Llama 4 Scout share?
11 benchmarks have published results for both models. Codellama 34b Instruct has 14 scored results on Noometry and Llama 4 Scout has 43.