Model comparison
DeepSeek-V3.2-Speciale vs Grok 4.7
Grok 4.7 is the stronger model overall, scoring 53.1 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 4.7's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
DeepSeekSummary
- They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 0 categories and Grok 4.7 in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Grok 4.7 leads 70.0 to 46.0.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $2 / $6 for Grok 4.7.
- Grok 4.7 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 4.7 | |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 39.7 | 53.1 |
| Released | 2025-12-01 | 2026-09-21 |
| 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 | 39 |
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Category by category
Coding Grok 4.7 leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Grok 4.7: 58.0 (#18)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| FrontierCode | — | 47.6% |
| CursorBench | — | 46.3% |
| LMArena WebDev | — | 1639 |
| FrontierSWE | — | 29.5% |
| SciCode | — | 57.8% |
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1427 |
Agentic & Tool Use Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.7: 36.7 (#37)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| APEX-Agents | — | 54.6% |
| GDP.pdf | — | 22.8% |
| Vending-Bench 2 | — | 10,537 |
Reasoning Grok 4.7 leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Grok 4.7: 49.1 (#40)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| SimpleBench | 52.6% | — |
| NYT Connections (extended) | — | 76.8% |
| CritPt | — | 18% |
| Chess Puzzles | — | 38% |
| LMArena Hard Prompts | — | 1413 |
| Mystery Game Puzzles | — | 29% |
| DTBench | — | 96% |
| LMCA | — | 49.4% |
| Epoch Capabilities Index | — | 153.53 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.7: 57.8 (#39)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 53% |
| FrontierMath Tier 4 | — | 17.1% |
| OTIS Mock AIME 2024-2025 | — | 98.1% |
| ProofBench | — | 34% |
| LMArena Math | — | 1407 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.7: 62.8 (#22)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| GPQA Diamond | — | 92.7% |
| SimpleQA Verified | — | 56% |
| LMArena Expert | — | 1422 |
Multimodal Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.7: 35.5 (#87)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| LMArena Vision | — | 1228 |
| Blueprint-Bench 2 | — | 32.5% |
| Furniture Assembly | — | 20.8% |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.7: 50.8 (#116)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| LMArena Non-English | — | 1389 |
| LMArena Chinese | — | 1455 |
| LMArena French | — | 1455 |
| LMArena Russian | — | 1397 |
| LMArena Spanish | — | 1400 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.7: 74.1 (#105)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| LMArena Instruction Following | — | 1404 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Grok 4.7: 43.1 (#104)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| LMArena Longer Query | — | 1413 |
Writing & Preference Grok 4.7 leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Grok 4.7: 70.0 (#24)
| Benchmark | DeepSeek-V3.2-Speciale | Grok 4.7 |
|---|---|---|
| EQ-Bench Creative Writing | 1276 | 2007 |
| LMArena Text | — | 1399 |
| LMArena Creative Writing | — | 1391 |
| LMArena Multi-Turn | — | 1393 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Grok 4.7?
Grok 4.7 is the stronger model overall, scoring 53.1 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 4.7's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-V3.2-Speciale or Grok 4.7?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Grok 4.7 lists at $2 and $6.
Is DeepSeek-V3.2-Speciale or Grok 4.7 better for coding?
Grok 4.7 scores higher on coding benchmarks: 58.0 versus 40.4 in the Noometry coding category.
Which has the bigger context window?
Grok 4.7 does, with 500K tokens against 128K.
How many benchmarks do DeepSeek-V3.2-Speciale and Grok 4.7 share?
1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Grok 4.7 has 39.