Model comparison
Devstral Small 2505 vs Llama 3.2 3B
Devstral Small 2505 is the stronger model overall, scoring 34.3 to 28.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in coding, where Devstral Small 2505 leads 38.9 to 27.6.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.10 / $0.30 for Devstral Small 2505.
- Llama 3.2 3B accepts more context: 131K tokens versus 128K.
Side by side
| Devstral Small 2505 | Llama 3.2 3B | |
|---|---|---|
| Provider | Mistral AI | Meta |
| Noometry Index | 34.3 | 28.9 |
| Released | 2025-05-07 | 2024-09-24 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 128K | 118K |
| Input $ / M tokens | $0.10 | $0.05 |
| Output $ / M tokens | $0.30 | $0.33 |
| Results tracked | 4 | 18 |
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Category by category
Coding Devstral Small 2505 leads
Devstral Small 2505: 38.9 (#166), Llama 3.2 3B: 27.6 (#319)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| SWE-bench Verified (bash only) | 56.4% | — |
| SciCode | 28.8% | — |
| BigCodeBench Instruct | — | 23.4% |
| LMArena Coding | — | 1098 |
| BigCodeBench Complete | — | 28.3% |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, Llama 3.2 3B: 20.1 (#143)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 21.9% |
| BALROG | — | 10.1% |
Reasoning Llama 3.2 3B leads
Devstral Small 2505: 19.7 (#252), Llama 3.2 3B: 21.0 (#228)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| Kagi LLM Benchmark | 37.7% | — |
| CritPt | 0% | — |
| LMArena Hard Prompts | — | 1095 |
Math Not comparable
Devstral Small 2505: —, Llama 3.2 3B: 32.4 (#214)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| LMArena Math | — | 1126 |
Knowledge Not comparable
Devstral Small 2505: —, Llama 3.2 3B: 29.7 (#235)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | — | 1090 |
Multilingual Not comparable
Devstral Small 2505: —, Llama 3.2 3B: 26.2 (#281)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | — | 1019 |
| LMArena Chinese | — | 1017 |
| LMArena German | — | 1056 |
| LMArena Russian | — | 949 |
Instruction Following Not comparable
Devstral Small 2505: —, Llama 3.2 3B: 56.0 (#275)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | — | 1089 |
Long Context Not comparable
Devstral Small 2505: —, Llama 3.2 3B: 33.4 (#261)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | — | 1100 |
Writing & Preference Not comparable
Devstral Small 2505: —, Llama 3.2 3B: 24.7 (#307)
| Benchmark | Devstral Small 2505 | Llama 3.2 3B |
|---|---|---|
| LMArena Text | — | 1110 |
| LMArena Creative Writing | — | 1094 |
| EQ-Bench Creative Writing | — | 595 |
| LMArena Multi-Turn | — | 1105 |
Frequently asked questions
Is Devstral Small 2505 better than Llama 3.2 3B?
Devstral Small 2505 is the stronger model overall, scoring 34.3 to 28.9 on the Noometry Index.
Which is cheaper, Devstral Small 2505 or Llama 3.2 3B?
Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; Devstral Small 2505 lists at $0.10 and $0.30.
Is Devstral Small 2505 or Llama 3.2 3B better for coding?
Devstral Small 2505 scores higher on coding benchmarks: 38.9 versus 27.6 in the Noometry coding category.
Which has the bigger context window?
Llama 3.2 3B does, with 131K tokens against 128K.
How many benchmarks do Devstral Small 2505 and Llama 3.2 3B share?
0 benchmarks have published results for both models. Devstral Small 2505 has 4 scored results on Noometry and Llama 3.2 3B has 18.