Model comparison
DeepSeek-V3.2-Speciale vs GPT-5.4 mini
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 39.1 on the Noometry Index. DeepSeek-V3.2-Speciale costs 2.0× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
DeepSeekSummary
- They share 2 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 1 category and GPT-5.4 mini in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.4 mini leads 64.2 to 46.1.
- The biggest single-benchmark swing is WeirdML: 46.7% for DeepSeek-V3.2-Speciale and 60.3% for GPT-5.4 mini.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $0.75 / $4.50 for GPT-5.4 mini.
- GPT-5.4 mini accepts more context: 400K tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | GPT-5.4 mini | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.1 | 44.8 |
| Released | 2025-12-01 | 2026-03-17 |
| Weights | Open | Proprietary |
| Context window | 128K | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $0.58 | $0.75 |
| Output $ / M tokens | $1.68 | $4.50 |
| Results tracked | 3 | 46 |
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Category by category
Coding GPT-5.4 mini leads
DeepSeek-V3.2-Speciale: 39.9 (#136), GPT-5.4 mini: 45.0 (#67)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| WeirdML | 46.7% | 60.3% |
| FrontierCode | — | 27% |
| LMArena WebDev | — | 1397 |
| SciCode | — | 49.9% |
| LMArena Coding | — | 1438 |
| ALE-Bench | — | 1,189 |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, GPT-5.4 mini: 29.6 (#74)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| DeepResearch Bench | — | 36.3% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), GPT-5.4 mini: 30.3 (#77)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| ARC-AGI-2 | — | 18.9% |
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 37.9% |
| NYT Connections (extended) | — | 61.8% |
| ARC-AGI-1 | — | 63.7% |
| CritPt | — | 10% |
| Chess Puzzles | — | 24% |
| Thematic Generalization | — | 61.7% |
| LMArena Hard Prompts | — | 1424 |
| Mystery Game Puzzles | — | 11% |
| DTBench | — | 80% |
| LMCA | — | 40.8% |
| Epoch Capabilities Index | — | 148.83 |
| ForecastBench | — | 57 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, GPT-5.4 mini: 45.4 (#63)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 51.2% |
| FrontierMath Tier 4 | — | 9.8% |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| ProofBench | — | 21% |
| LMArena Math | — | 1418 |
| FrontierMath (Feb 2025 set) | — | 28.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, GPT-5.4 mini: 51.4 (#62)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| GPQA Diamond | — | 86.9% |
| SimpleQA Verified | — | 29.4% |
| Vectara Hallucination Rate | — | 5.5% |
| LMArena Expert | — | 1434 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, GPT-5.4 mini: 39.0 (#51)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| LMArena Vision | — | 1245 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, GPT-5.4 mini: 52.1 (#94)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| LMArena Non-English | — | 1405 |
| LMArena Chinese | — | 1446 |
| LMArena French | — | 1440 |
| LMArena German | — | 1407 |
| LMArena Japanese | — | 1375 |
| LMArena Korean | — | 1369 |
| LMArena Russian | — | 1417 |
| LMArena Spanish | — | 1403 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, GPT-5.4 mini: 74.3 (#99)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| LMArena Instruction Following | — | 1405 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, GPT-5.4 mini: 42.9 (#107)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| LMArena Longer Query | — | 1407 |
Writing & Preference GPT-5.4 mini leads
DeepSeek-V3.2-Speciale: 46.1 (#217), GPT-5.4 mini: 64.2 (#56)
| Benchmark | DeepSeek-V3.2-Speciale | GPT-5.4 mini |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 1665 |
| LMArena Text | — | 1411 |
| LMArena Creative Writing | — | 1370 |
| LMArena Multi-Turn | — | 1429 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than GPT-5.4 mini?
GPT-5.4 mini is the stronger model overall, scoring 44.8 to 39.1 on the Noometry Index. DeepSeek-V3.2-Speciale costs 2.0× less per token, which makes it the better buy when GPT-5.4 mini's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.2-Speciale or GPT-5.4 mini?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; GPT-5.4 mini lists at $0.75 and $4.50.
Is DeepSeek-V3.2-Speciale or GPT-5.4 mini better for coding?
GPT-5.4 mini scores higher on coding benchmarks: 45.0 versus 39.9 in the Noometry coding category.
Which has the bigger context window?
GPT-5.4 mini does, with 400K tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and GPT-5.4 mini share?
2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and GPT-5.4 mini has 46.