Model comparison
DeepSeek-V3.2-Speciale vs Grok 4.5
Grok 4.5 is the stronger model overall, scoring 55.0 to 39.7 on the Noometry Index. DeepSeek-V3.2-Speciale costs 3.5× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
DeepSeekSummary
- They share 3 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 0 categories and Grok 4.5 in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.1 to 32.9.
- The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 70% for Grok 4.5.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $2 / $6 for Grok 4.5.
- Grok 4.5 accepts more context: 500K tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | Grok 4.5 | |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 39.7 | 55.0 |
| Released | 2025-12-01 | 2026-07-08 |
| Weights | Open | Proprietary |
| Context window | 128K | 500K |
| Max output | 128K | 500K |
| Input $ / M tokens | $0.58 | $2 |
| Output $ / M tokens | $1.68 | $6 |
| Results tracked | 3 | 52 |
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Category by category
Coding Grok 4.5 leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Grok 4.5: 52.2 (#35)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| WeirdML | 46.7% | 46.4% |
| DeepSWE | — | 53.8% |
| FrontierCode | — | 42.4% |
| LMArena WebDev | — | 1553 |
| SciCode | — | 54.1% |
| LMArena Coding | — | 1474 |
| ALE-Bench | — | 1,309 |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.5: 44.4 (#17)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| APEX-Agents | — | 56.2% |
| τ²-bench Banking | — | 47.9% |
| PostTrainBench | — | 23.4% |
| GBAEval | — | 65.4% |
| GDP.pdf | — | 14% |
| LMArena Search | — | 1213 |
| Vending-Bench 2 | — | 3,887 |
Reasoning Grok 4.5 leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Grok 4.5: 56.1 (#25)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| SimpleBench | 52.6% | 70% |
| ARC-AGI-2 | — | 52.6% |
| Kagi LLM Benchmark | — | 83.5% |
| NYT Connections (extended) | — | 79.9% |
| ARC-AGI-1 | — | 87.2% |
| CritPt | — | 15.4% |
| Chess Puzzles | — | 36% |
| LMArena Hard Prompts | — | 1462 |
| DTBench | — | 96.5% |
| LMCA | — | 45.2% |
| Surface Evolver Bench | — | 74.4% |
| Epoch Capabilities Index | — | 153.92 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.5: 60.9 (#35)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 24.4% |
| OTIS Mock AIME 2024-2025 | — | 97.8% |
| ProofBench | — | 31% |
| LMArena Math | — | 1459 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.5: 62.3 (#24)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| GPQA Diamond | — | 93.4% |
| SimpleQA Verified | — | 48.3% |
| LMArena Expert | — | 1466 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.5: 37.6 (#72)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| LMArena Vision | — | 1288 |
| Blueprint-Bench 2 | — | 27.3% |
| Furniture Assembly | — | 22.5% |
| LMArena Document | — | 1452 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.5: 54.4 (#42)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| LMArena Non-English | — | 1440 |
| LMArena Chinese | — | 1496 |
| LMArena French | — | 1456 |
| LMArena German | — | 1446 |
| LMArena Japanese | — | 1428 |
| LMArena Korean | — | 1404 |
| LMArena Russian | — | 1448 |
| LMArena Spanish | — | 1450 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.5: 76.0 (#48)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| LMArena Instruction Following | — | 1446 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.5: 44.8 (#56)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| LMArena Longer Query | — | 1463 |
Writing & Preference Grok 4.5 leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Grok 4.5: 65.8 (#42)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.5 |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 1579 |
| LMArena Text | — | 1448 |
| LMArena Creative Writing | — | 1442 |
| LMArena Multi-Turn | — | 1456 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Grok 4.5?
Grok 4.5 is the stronger model overall, scoring 55.0 to 39.7 on the Noometry Index. DeepSeek-V3.2-Speciale costs 3.5× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.2-Speciale or Grok 4.5?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Grok 4.5 lists at $2 and $6.
Is DeepSeek-V3.2-Speciale or Grok 4.5 better for coding?
Grok 4.5 scores higher on coding benchmarks: 52.2 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
Grok 4.5 does, with 500K tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and Grok 4.5 share?
3 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Grok 4.5 has 52.