Model comparison
DeepSeek Coder 1.3B vs Llama 4 Scout
Llama 4 Scout has enough public results to be ranked (#330); DeepSeek Coder 1.3B does not yet, so treat this comparison as directional.
Last verified . 2 shared benchmarks.
DeepSeek
MetaSummary
- They share 2 benchmarks with published results for both. DeepSeek Coder 1.3B scores higher in 1 category and Llama 4 Scout in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in coding, where DeepSeek Coder 1.3B leads 31.2 to 20.2.
- The biggest single-benchmark swing is BigCodeBench Complete: 29.6% for DeepSeek Coder 1.3B and 43.1% for Llama 4 Scout.
Side by side
| DeepSeek Coder 1.3B | Llama 4 Scout | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 35.0 | 27.7 |
| Released | 2023-11-02 | 2025-04-05 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.10 |
| Output $ / M tokens | — | $0.30 |
| Results tracked | 9 | 43 |
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Category by category
Coding DeepSeek Coder 1.3B leads
DeepSeek Coder 1.3B: 31.2 (#287), Llama 4 Scout: 20.2 (#339)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| BigCodeBench Complete | 29.6% | 43.1% |
| SWE-bench Verified (bash only) | — | 9.1% |
| SciCode | — | 17% |
| BigCodeBench Instruct | 22.8% | — |
| LMArena Coding | — | 1286 |
| HumanEval+ | 60.4% | — |
| MBPP+ | 54.8% | — |
Agentic & Tool Use Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 24.6 (#119)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 9.1 (#345)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| Epoch Capabilities Index | 63.6 | 129.64 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| CritPt | — | 0% |
| LMArena Hard Prompts | — | 1266 |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| ForecastBench | — | 57.5 |
| WinoGrande | 53.3% | — |
Math Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 19.6 (#286)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| LMArena Math | — | 1287 |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
| GSM8K | 4.4% | — |
Knowledge Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 31.9 (#217)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
| LMArena Expert | — | 1235 |
| ARC (AI2) Challenge | 25.4% | — |
| MMLU | 25.8% | — |
Multimodal Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 32.2 (#102)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 41.0 (#212)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | — | 1252 |
| LMArena Chinese | — | 1255 |
| LMArena French | — | 1282 |
| LMArena German | — | 1272 |
| LMArena Japanese | — | 1206 |
| LMArena Korean | — | 1207 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1278 |
Instruction Following Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 65.8 (#217)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| IFEval | — | 81.8% |
| LMArena Instruction Following | — | 1248 |
Long Context Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 27.5 (#294)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| Fiction.LiveBench | — | 36% |
| LMArena Longer Query | — | 1265 |
Writing & Preference Not comparable
DeepSeek Coder 1.3B: —, Llama 4 Scout: 37.0 (#261)
| Benchmark | DeepSeek Coder 1.3B | Llama 4 Scout |
|---|---|---|
| LMArena Text | — | 1279 |
| LMArena Creative Writing | — | 1249 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
| LMArena Multi-Turn | — | 1280 |
Frequently asked questions
Is DeepSeek Coder 1.3B better than Llama 4 Scout?
Llama 4 Scout has enough public results to be ranked (#330); DeepSeek Coder 1.3B does not yet, so treat this comparison as directional.
Is DeepSeek Coder 1.3B or Llama 4 Scout better for coding?
DeepSeek Coder 1.3B scores higher on coding benchmarks: 31.2 versus 20.2 in the Noometry coding category.
How many benchmarks do DeepSeek Coder 1.3B and Llama 4 Scout share?
2 benchmarks have published results for both models. DeepSeek Coder 1.3B has 9 scored results on Noometry and Llama 4 Scout has 43.