Model comparison
DeepSeek-V3.2-Speciale vs Gemini 3 Flash Preview
Gemini 3 Flash Preview is the stronger model overall, scoring 52.3 to 39.7 on the Noometry Index.
Last verified . 2 shared benchmarks.
DeepSeek
GoogleSummary
- They share 2 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 0 categories and Gemini 3 Flash Preview in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Gemini 3 Flash Preview leads 65.5 to 46.0.
- The biggest single-benchmark swing is WeirdML: 46.7% for DeepSeek-V3.2-Speciale and 61.6% for Gemini 3 Flash Preview.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $0.50 / $3 for Gemini 3 Flash Preview.
- Gemini 3 Flash Preview accepts more context: 1.05M tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 39.7 | 52.3 |
| Released | 2025-12-01 | 2025-12-17 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.58 | $0.50 |
| Output $ / M tokens | $1.68 | $3 |
| Results tracked | 3 | 59 |
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Category by category
Coding Gemini 3 Flash Preview leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Gemini 3 Flash Preview: 50.9 (#42)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| WeirdML | 46.7% | 61.6% |
| SWE-bench Verified | — | 75.4% |
| SWE-bench Verified (bash only) | — | 75.8% |
| LMArena WebDev | — | 1439 |
| SWE-bench Multilingual | — | 72.7% |
| GSO | — | 9.8% |
| LMArena Coding | — | 1460 |
| ALE-Bench | — | 1,367 |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3 Flash Preview: 38.7 (#29)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| Terminal-Bench | — | 64.3% |
| τ²-bench Airline | — | 82.5% |
| τ²-bench Banking | — | 27.3% |
| τ²-bench Retail | — | 76.8% |
| τ²-bench Telecom | — | 91.2% |
| DeepResearch Bench | — | 49.8% |
| BALROG | — | 48.1% |
| GDP.pdf | — | 10% |
| LMArena Search | — | 1198 |
| Vending-Bench 2 | — | 3,635 |
Reasoning Gemini 3 Flash Preview leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Gemini 3 Flash Preview: 49.2 (#37)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| SimpleBench | 52.6% | 61.1% |
| ARC-AGI-2 | — | 33.6% |
| NYT Connections (extended) | — | 83.1% |
| ARC-AGI-1 | — | 84.7% |
| Chess Puzzles | — | 40% |
| LMArena Hard Prompts | — | 1465 |
| Mystery Game Puzzles | — | 26% |
| DTBench | — | 89.1% |
| LMCA | — | 43.1% |
| Epoch Capabilities Index | — | 151.8 |
| ForecastBench | — | 58.5 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3 Flash Preview: 51.7 (#55)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 51.2% |
| FrontierMath Tier 4 | — | 17.1% |
| MathArena Final-Answer Competitions | — | 67.6% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| ProofBench | — | 15% |
| LMArena Math | — | 1473 |
| FrontierMath (Feb 2025 set) | — | 35.6% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3 Flash Preview: 58.8 (#33)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| GPQA Diamond | — | 89.4% |
| SimpleQA Verified | — | 66.8% |
| Vectara Hallucination Rate | — | 13.5% |
| LMArena Expert | — | 1462 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3 Flash Preview: 45.5 (#16)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| LMArena Vision | — | 1285 |
| GeoBench | — | 88% |
| VPCT | — | 72.6% |
| Blueprint-Bench 2 | — | 0% |
| LMArena Document | — | 1413 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3 Flash Preview: 55.7 (#27)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| LMArena Non-English | — | 1458 |
| LMArena Chinese | — | 1511 |
| LMArena French | — | 1477 |
| LMArena German | — | 1497 |
| LMArena Japanese | — | 1489 |
| LMArena Korean | — | 1443 |
| LMArena Russian | — | 1480 |
| LMArena Spanish | — | 1469 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3 Flash Preview: 75.7 (#56)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| LMArena Instruction Following | — | 1437 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3 Flash Preview: 44.4 (#67)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| LMArena Longer Query | — | 1452 |
Writing & Preference Gemini 3 Flash Preview leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Gemini 3 Flash Preview: 65.5 (#45)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3 Flash Preview |
|---|---|---|
| LMArena Text | — | 1466 |
| LMArena Creative Writing | — | 1457 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1471 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Gemini 3 Flash Preview?
Gemini 3 Flash Preview is the stronger model overall, scoring 52.3 to 39.7 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or Gemini 3 Flash Preview?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Gemini 3 Flash Preview lists at $0.50 and $3.
Is DeepSeek-V3.2-Speciale or Gemini 3 Flash Preview better for coding?
Gemini 3 Flash Preview scores higher on coding benchmarks: 50.9 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
Gemini 3 Flash Preview does, with 1.05M tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and Gemini 3 Flash Preview share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemini 3 Flash Preview has 59.