Model comparison
DeepSeek-V3.2-Speciale vs GPT-4.1 mini
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 33.5 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 2 categories and GPT-4.1 mini in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 10.9.
- The biggest single-benchmark swing is WeirdML: 46.7% for DeepSeek-V3.2-Speciale and 37.6% for GPT-4.1 mini.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- GPT-4.1 mini 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 | GPT-4.1 mini | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.1 | 33.5 |
| Released | 2025-12-01 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 128K | 33K |
| Input $ / M tokens | $0.58 | $0.40 |
| Output $ / M tokens | $1.68 | $1.60 |
| Results tracked | 3 | 47 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 39.9 (#136), GPT-4.1 mini: 30.4 (#286)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| WeirdML | 46.7% | 37.6% |
| SWE-bench Verified (bash only) | — | 23.9% |
| Aider Polyglot | — | 32.4% |
| SciCode | — | 40.4% |
| BigCodeBench Instruct | — | 48.9% |
| LMArena Coding | — | 1367 |
| CadEval | — | 16% |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4.1 mini: 33.0 (#52)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 50.5% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), GPT-4.1 mini: 10.9 (#335)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| ARC-AGI-2 | — | 0% |
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 48.6% |
| ARC-AGI-1 | — | 3.5% |
| CritPt | — | 0% |
| Chess Puzzles | — | 7% |
| LMArena Hard Prompts | — | 1349 |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 68.8% |
| LMCA | — | 21.1% |
| Epoch Capabilities Index | — | 135.01 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4.1 mini: 23.1 (#264)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 6.7% |
| OTIS Mock AIME 2024-2025 | — | 44.7% |
| Omni-MATH | — | 49.1% |
| LMArena Math | — | 1343 |
| MATH Level 5 | — | 87.3% |
| FrontierMath (Feb 2025 set) | — | 4.5% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4.1 mini: 34.7 (#183)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| GPQA Diamond | — | 65.8% |
| SimpleQA Verified | — | 12.7% |
| MMLU-Pro | — | 78.3% |
| GPQA (HELM) | — | 61.4% |
| LMArena Expert | — | 1338 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4.1 mini: 35.2 (#77)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | — | 1181 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4.1 mini: 45.9 (#161)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | — | 1318 |
| LMArena Chinese | — | 1329 |
| LMArena French | — | 1357 |
| LMArena German | — | 1349 |
| LMArena Japanese | — | 1291 |
| LMArena Korean | — | 1298 |
| LMArena Russian | — | 1324 |
| LMArena Spanish | — | 1319 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4.1 mini: 73.9 (#113)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| IFEval | — | 90.4% |
| LMArena Instruction Following | — | 1332 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, GPT-4.1 mini: 31.8 (#270)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| Fiction.LiveBench | — | 44.4% |
| LMArena Longer Query | — | 1344 |
Writing & Preference GPT-4.1 mini leads
DeepSeek-V3.2-Speciale: 46.1 (#217), GPT-4.1 mini: 48.8 (#193)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-4.1 mini |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 1147 |
| LMArena Text | — | 1341 |
| LMArena Creative Writing | — | 1300 |
| WildBench | — | 83.8% |
| LMArena Multi-Turn | — | 1354 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than GPT-4.1 mini?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 33.5 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or GPT-4.1 mini?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.
Is DeepSeek-V3.2-Speciale or GPT-4.1 mini better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 30.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and GPT-4.1 mini share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and GPT-4.1 mini has 47.