Model comparison
Devstral Small 2505 vs Llama 4 Scout
Devstral Small 2505 is the stronger model overall, scoring 33.9 to 27.4 on the Noometry Index.
Last verified . 4 shared benchmarks.
Mistral AI
MetaSummary
- They share 4 benchmarks with published results for both. Devstral Small 2505 scores higher in 2 categories and Llama 4 Scout in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Devstral Small 2505 leads 38.6 to 19.9.
- The biggest single-benchmark swing is SWE-bench Verified (bash only): 56.4% for Devstral Small 2505 and 9.1% for Llama 4 Scout.
- Both cost about the same: $0.10 input and $0.30 output per million tokens.
Side by side
| Devstral Small 2505 | Llama 4 Scout | |
|---|---|---|
| Provider | Mistral AI | Meta |
| Noometry Index | 33.9 | 27.4 |
| Released | 2025-05-07 | 2025-04-05 |
| Weights | Open | Open |
| Context window | 128K | 128K |
| Max output | 128K | 4K |
| Input $ / M tokens | $0.10 | $0.10 |
| Output $ / M tokens | $0.30 | $0.30 |
| Results tracked | 4 | 43 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Devstral Small 2505 leads
Devstral Small 2505: 38.6 (#160), Llama 4 Scout: 19.9 (#334)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| SWE-bench Verified (bash only) | 56.4% | 9.1% |
| SciCode | 28.8% | 17% |
| LMArena Coding | — | 1286 |
| BigCodeBench Complete | — | 43.1% |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, Llama 4 Scout: 24.4 (#109)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.1% |
Reasoning Devstral Small 2505 leads
Devstral Small 2505: 19.1 (#243), Llama 4 Scout: 9.2 (#339)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| Kagi LLM Benchmark | 37.7% | 36.9% |
| CritPt | 0% | 0% |
| ARC-AGI-2 | — | 0% |
| ARC-AGI-1 | — | 0.5% |
| LMArena Hard Prompts | — | 1266 |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| Epoch Capabilities Index | — | 129.64 |
| ForecastBench | — | 57.5 |
Math Not comparable
Devstral Small 2505: —, Llama 4 Scout: 18.4 (#280)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 7.8% |
| Omni-MATH | — | 37.3% |
| LMArena Math | — | 1286 |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |
Knowledge Not comparable
Devstral Small 2505: —, Llama 4 Scout: 31.8 (#208)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | — | 51.8% |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
| LMArena Expert | — | 1236 |
Multimodal Not comparable
Devstral Small 2505: —, Llama 4 Scout: 31.6 (#98)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| SpatialViz-Bench | — | 34.2% |
Multilingual Not comparable
Devstral Small 2505: —, Llama 4 Scout: 41.3 (#207)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | — | 1253 |
| LMArena Chinese | — | 1256 |
| LMArena French | — | 1283 |
| LMArena German | — | 1274 |
| LMArena Japanese | — | 1209 |
| LMArena Korean | — | 1207 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1277 |
Instruction Following Not comparable
Devstral Small 2505: —, Llama 4 Scout: 66.0 (#212)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| IFEval | — | 81.8% |
| LMArena Instruction Following | — | 1248 |
Long Context Not comparable
Devstral Small 2505: —, Llama 4 Scout: 27.5 (#289)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| Fiction.LiveBench | — | 36% |
| LMArena Longer Query | — | 1265 |
Writing & Preference Not comparable
Devstral Small 2505: —, Llama 4 Scout: 37.1 (#256)
| Benchmark | Devstral Small 2505 | Llama 4 Scout |
|---|---|---|
| LMArena Text | — | 1279 |
| LMArena Creative Writing | — | 1249 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
| LMArena Multi-Turn | — | 1281 |
Frequently asked questions
Is Devstral Small 2505 better than Llama 4 Scout?
Devstral Small 2505 is the stronger model overall, scoring 33.9 to 27.4 on the Noometry Index.
Which is cheaper, Devstral Small 2505 or Llama 4 Scout?
Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Devstral Small 2505 lists at $0.10 and $0.30.
Is Devstral Small 2505 or Llama 4 Scout better for coding?
Devstral Small 2505 scores higher on coding benchmarks: 38.6 versus 19.9 in the Noometry coding category.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do Devstral Small 2505 and Llama 4 Scout share?
4 benchmarks have published results for both models. Devstral Small 2505 has 4 scored results on Noometry and Llama 4 Scout has 43.