Model comparison
DeepSeek-V3.2-Speciale vs DeepSeek V4 Pro
DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 39.1 on the Noometry Index.
Last verified . 2 shared benchmarks.
DeepSeekSummary
- They share 2 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 0 categories and DeepSeek V4 Pro in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.4 to 32.1.
- The biggest single-benchmark swing is WeirdML: 46.7% for DeepSeek-V3.2-Speciale and 66.2% for DeepSeek V4 Pro.
- DeepSeek V4 Pro is cheaper at $0.43 / $0.87 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 128K.
Side by side
| DeepSeek-V3.2-Speciale | DeepSeek V4 Pro | |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Noometry Index | 39.1 | 54.2 |
| Released | 2025-12-01 | 2026-04-24 |
| Weights | Open | Open |
| Context window | 128K | 1M |
| Max output | 128K | 393K |
| Input $ / M tokens | $0.58 | $0.43 |
| Output $ / M tokens | $1.68 | $0.87 |
| Results tracked | 3 | 48 |
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Category by category
Coding DeepSeek V4 Pro leads
DeepSeek-V3.2-Speciale: 39.9 (#136), DeepSeek V4 Pro: 52.2 (#31)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| WeirdML | 46.7% | 66.2% |
| SWE-bench Verified | — | 77.6% |
| FrontierCode | — | 28.6% |
| LMArena WebDev | — | 1582 |
| SciCode | — | 51% |
| LMArena Coding | — | 1470 |
| ALE-Bench | — | 1,403 |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, DeepSeek V4 Pro: 32.7 (#54)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| APEX-Agents | — | 47.3% |
| Vending-Bench 2 | — | 3,285 |
Reasoning DeepSeek V4 Pro leads
DeepSeek-V3.2-Speciale: 32.1 (#65), DeepSeek V4 Pro: 56.4 (#22)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| ARC-AGI-2 | — | 61.3% |
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 53.5% |
| NYT Connections (extended) | — | 91.3% |
| ARC-AGI-1 | — | 90.5% |
| CritPt | — | 18% |
| Chess Puzzles | — | 47% |
| LMArena Hard Prompts | — | 1461 |
| Mystery Game Puzzles | — | 43% |
| DTBench | — | 93.9% |
| LMCA | — | 45.5% |
| Surface Evolver Bench | — | 40% |
| Epoch Capabilities Index | — | 155.39 |
| ForecastBench | — | 56.1 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, DeepSeek V4 Pro: 64.6 (#24)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 64.6% |
| FrontierMath Tier 4 | — | 26.8% |
| MathArena Final-Answer Competitions | — | 76.6% |
| OTIS Mock AIME 2024-2025 | — | 98.6% |
| ProofBench | — | 50% |
| LMArena Math | — | 1455 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, DeepSeek V4 Pro: 59.5 (#28)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| GPQA Diamond | — | 91.7% |
| SimpleQA Verified | — | 52.9% |
| Vectara Hallucination Rate | — | 8.6% |
| LMArena Expert | — | 1463 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, DeepSeek V4 Pro: 54.5 (#44)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| LMArena Non-English | — | 1438 |
| LMArena Chinese | — | 1486 |
| LMArena French | — | 1473 |
| LMArena German | — | 1458 |
| LMArena Japanese | — | 1448 |
| LMArena Korean | — | 1452 |
| LMArena Russian | — | 1452 |
| LMArena Spanish | — | 1457 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, DeepSeek V4 Pro: 76.3 (#44)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| LMArena Instruction Following | — | 1448 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, DeepSeek V4 Pro: 45.0 (#49)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| CL-bench Life | — | 13.5% |
| LMArena Longer Query | — | 1459 |
Writing & Preference DeepSeek V4 Pro leads
DeepSeek-V3.2-Speciale: 46.1 (#217), DeepSeek V4 Pro: 65.6 (#45)
| Benchmark | DeepSeek-V3.2-Speciale | DeepSeek V4 Pro |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 1553 |
| LMArena Text | — | 1451 |
| LMArena Creative Writing | — | 1446 |
| EQ-Bench 4 | — | 1166 |
| LMArena Multi-Turn | — | 1467 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than DeepSeek V4 Pro?
DeepSeek V4 Pro is the stronger model overall, scoring 54.2 to 39.1 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or DeepSeek V4 Pro?
DeepSeek V4 Pro is cheaper. It lists at $0.43 per million input tokens and $0.87 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.
Is DeepSeek-V3.2-Speciale or DeepSeek V4 Pro better for coding?
DeepSeek V4 Pro scores higher on coding benchmarks: 52.2 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Pro does, with 1M tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and DeepSeek V4 Pro share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and DeepSeek V4 Pro has 48.