Model comparison
DeepSeek-V3.2-Speciale vs Magistral Medium
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 34.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Mistral AISummary
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 8.7.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $2 / $5 for Magistral Medium.
Side by side
| DeepSeek-V3.2-Speciale | Magistral Medium | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 39.1 | 34.8 |
| Released | 2025-12-01 | 2025-03-17 |
| Weights | Open | Open |
| Context window | 128K | 128K |
| Max output | 128K | 16K |
| Input $ / M tokens | $0.58 | $2 |
| Output $ / M tokens | $1.68 | $5 |
| Results tracked | 3 | 22 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 39.9 (#136), Magistral Medium: 38.6 (#161)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| SciCode | — | 39.2% |
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1319 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), Magistral Medium: 8.7 (#342)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| ARC-AGI-2 | — | 0% |
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 16.2% |
| ARC-AGI-1 | — | 6.1% |
| CritPt | — | 0.3% |
| LMArena Hard Prompts | — | 1267 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Magistral Medium: 32.4 (#187)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| LMArena Math | — | 1249 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Magistral Medium: 32.9 (#199)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| LMArena Expert | — | 1222 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Magistral Medium: 39.8 (#219)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| LMArena Non-English | — | 1232 |
| LMArena Chinese | — | 1225 |
| LMArena French | — | 1268 |
| LMArena German | — | 1248 |
| LMArena Japanese | — | 1176 |
| LMArena Korean | — | 1125 |
| LMArena Russian | — | 1224 |
| LMArena Spanish | — | 1269 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Magistral Medium: 66.2 (#207)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| LMArena Instruction Following | — | 1254 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Magistral Medium: 39.3 (#178)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| LMArena Longer Query | — | 1295 |
Writing & Preference Too close to call
DeepSeek-V3.2-Speciale: 46.1 (#217), Magistral Medium: 46.5 (#214)
| Benchmark | DeepSeek-V3.2-Speciale | Magistral Medium |
|---|---|---|
| LMArena Text | — | 1255 |
| LMArena Creative Writing | — | 1245 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1275 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Magistral Medium?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 34.8 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or Magistral Medium?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Magistral Medium lists at $2 and $5.
Is DeepSeek-V3.2-Speciale or Magistral Medium better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 38.6 in the Noometry coding category.
Which has the bigger context window?
Both accept 128K tokens.
How many benchmarks do DeepSeek-V3.2-Speciale and Magistral Medium share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Magistral Medium has 22.