Model comparison
DeepSeek-V3.2-Speciale vs Gemini 3.5 Flash
Gemini 3.5 Flash is the stronger model overall, scoring 54.1 to 39.1 on the Noometry Index. DeepSeek-V3.2-Speciale costs 3.9× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.
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 3.5 Flash in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.5 Flash leads 62.7 to 32.1.
- The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 76.7% for Gemini 3.5 Flash.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $1.50 / $9 for Gemini 3.5 Flash.
- Gemini 3.5 Flash 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 3.5 Flash | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 39.1 | 54.1 |
| Released | 2025-12-01 | 2026-05-19 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 128K | 66K |
| Input $ / M tokens | $0.58 | $1.50 |
| Output $ / M tokens | $1.68 | $9 |
| Results tracked | 3 | 54 |
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Category by category
Coding Gemini 3.5 Flash leads
DeepSeek-V3.2-Speciale: 39.9 (#136), Gemini 3.5 Flash: 49.1 (#46)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| WeirdML | 46.7% | 62.6% |
| SWE-bench Verified | — | 79.3% |
| DeepSWE | — | 37.4% |
| LMArena WebDev | — | 1499 |
| SciCode | — | 53.1% |
| LMArena Coding | — | 1492 |
| ALE-Bench | — | 911.02 |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3.5 Flash: 24.8 (#107)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| APEX-Agents | — | 27.5% |
| GBAEval | — | 6.7% |
| GDP.pdf | — | 14% |
| Vending-Bench 2 | — | 5,396 |
Reasoning Gemini 3.5 Flash leads
DeepSeek-V3.2-Speciale: 32.1 (#65), Gemini 3.5 Flash: 62.7 (#16)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| SimpleBench | 52.6% | 76.7% |
| ARC-AGI-2 | — | 72.1% |
| NYT Connections (extended) | — | 92.6% |
| ARC-AGI-1 | — | 92.5% |
| CritPt | — | 13.1% |
| Chess Puzzles | — | 50% |
| EnigmaEval | — | 25.4% |
| EBR-Bench | — | 4.8% |
| LMArena Hard Prompts | — | 1488 |
| Mystery Game Puzzles | — | 32% |
| DTBench | — | 94.7% |
| LMCA | — | 47.1% |
| Surface Evolver Bench | — | 58.1% |
| Epoch Capabilities Index | — | 154.55 |
| ForecastBench | — | 59 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3.5 Flash: 60.5 (#30)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 62.8% |
| FrontierMath Tier 4 | — | 26.8% |
| MathArena Final-Answer Competitions | — | 76.3% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| ProofBench | — | 31% |
| LMArena Math | — | 1502 |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3.5 Flash: 66.3 (#10)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| GPQA Diamond | — | 92.8% |
| SimpleQA Verified | — | 66.2% |
| LMArena Expert | — | 1493 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3.5 Flash: 45.7 (#13)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| LMArena Vision | — | 1311 |
| Blueprint-Bench 2 | — | 33.6% |
| LMArena Document | — | 1463 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3.5 Flash: 57.1 (#12)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| LMArena Non-English | — | 1475 |
| LMArena Chinese | — | 1525 |
| LMArena French | — | 1490 |
| LMArena German | — | 1500 |
| LMArena Japanese | — | 1481 |
| LMArena Korean | — | 1453 |
| LMArena Russian | — | 1491 |
| LMArena Spanish | — | 1478 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3.5 Flash: 77.2 (#29)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| LMArena Instruction Following | — | 1466 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Gemini 3.5 Flash: 45.3 (#39)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| LMArena Longer Query | — | 1481 |
Writing & Preference Gemini 3.5 Flash leads
DeepSeek-V3.2-Speciale: 46.1 (#217), Gemini 3.5 Flash: 65.5 (#46)
| Benchmark | DeepSeek-V3.2-Speciale | Gemini 3.5 Flash |
|---|---|---|
| LMArena Text | — | 1481 |
| LMArena Creative Writing | — | 1467 |
| EQ-Bench Creative Writing | 1276 | — |
| EQ-Bench 4 | — | 1087 |
| LMArena Multi-Turn | — | 1482 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Gemini 3.5 Flash?
Gemini 3.5 Flash is the stronger model overall, scoring 54.1 to 39.1 on the Noometry Index. DeepSeek-V3.2-Speciale costs 3.9× less per token, which makes it the better buy when Gemini 3.5 Flash's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.2-Speciale or Gemini 3.5 Flash?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Gemini 3.5 Flash lists at $1.50 and $9.
Is DeepSeek-V3.2-Speciale or Gemini 3.5 Flash better for coding?
Gemini 3.5 Flash scores higher on coding benchmarks: 49.1 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.5 Flash does, with 1.05M tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and Gemini 3.5 Flash share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemini 3.5 Flash has 54.