Model comparison
DeepSeek-V3.2-Speciale vs Gemini 1.5 Flash 8B
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 29.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
GoogleSummary
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 19.2.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 39.1 | 29.7 |
| Released | 2025-12-01 | 2024-10-03 |
| Weights | Open | Proprietary |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 21 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 39.9 (#136), Gemini 1.5 Flash 8B: 34.9 (#221)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1218 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), Gemini 1.5 Flash 8B: 19.2 (#242)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1210 |
| DTBench | — | 50% |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Flash 8B: 13.3 (#296)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 4.6% |
| LMArena Math | — | 1207 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Flash 8B: 16.0 (#285)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| GPQA Diamond | — | 33% |
| LMArena Expert | — | 1185 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Flash 8B: 27.6 (#110)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| LMArena Vision | — | 1044 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Flash 8B: 38.6 (#224)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| LMArena Non-English | — | 1215 |
| LMArena Chinese | — | 1231 |
| LMArena French | — | 1233 |
| LMArena German | — | 1206 |
| LMArena Japanese | — | 1150 |
| LMArena Korean | — | 1140 |
| LMArena Russian | — | 1236 |
| LMArena Spanish | — | 1212 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Flash 8B: 63.1 (#231)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| LMArena Instruction Following | — | 1199 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 1.5 Flash 8B: 36.9 (#220)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| LMArena Longer Query | — | 1219 |
Writing & Preference DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 46.1 (#217), Gemini 1.5 Flash 8B: 43.0 (#227)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 1.5 Flash 8B |
|---|---|---|
| LMArena Text | — | 1226 |
| LMArena Creative Writing | — | 1218 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1185 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Gemini 1.5 Flash 8B?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 29.7 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Gemini 1.5 Flash 8B better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 34.9 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Gemini 1.5 Flash 8B share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemini 1.5 Flash 8B has 21.