Model comparison
DeepSeek-V3.2-Speciale vs Olmo 3.1 32b Think
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 37.3 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Allen Institute for AI (Ai2)Summary
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 24.1.
Side by side
| DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think | |
|---|---|---|
| Provider | DeepSeek | Allen Institute for AI (Ai2) |
| Noometry Index | 39.1 | 37.3 |
| Released | 2025-12-01 | — |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 15 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 39.9 (#136), Olmo 3.1 32b Think: 37.1 (#186)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1292 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), Olmo 3.1 32b Think: 24.1 (#151)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1272 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Olmo 3.1 32b Think: 33.6 (#170)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Math | — | 1305 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Olmo 3.1 32b Think: 35.0 (#178)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Expert | — | 1294 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Olmo 3.1 32b Think: 38.3 (#226)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Non-English | — | 1210 |
| LMArena Chinese | — | 1241 |
| LMArena French | — | 1262 |
| LMArena German | — | 1260 |
| LMArena Russian | — | 1193 |
| LMArena Spanish | — | 1288 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Olmo 3.1 32b Think: 65.8 (#213)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Instruction Following | — | 1246 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Olmo 3.1 32b Think: 38.6 (#190)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Longer Query | — | 1272 |
Writing & Preference Too close to call
DeepSeek-V3.2-Speciale: 46.1 (#217), Olmo 3.1 32b Think: 46.4 (#215)
| Benchmark | DeepSeek-V3.2-Speciale | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Text | — | 1271 |
| LMArena Creative Writing | — | 1226 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1252 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Olmo 3.1 32b Think?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 37.3 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Olmo 3.1 32b Think better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 37.1 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Olmo 3.1 32b Think share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Olmo 3.1 32b Think has 15.