# DeepSeek-V3.2-Exp vs Grok 4.1 Fast

> DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 41.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-exp-vs-grok-4-1-fast
- Last updated: 2026-10-12
- Shared benchmarks: 26

## Summary

- They share 26 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 7 categories and Grok 4.1 Fast in 2 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.1 Fast leads 43.4 to 22.1.
- The biggest single-benchmark swing is NYT Connections (extended): 36.7% for DeepSeek-V3.2-Exp and 87.4% for Grok 4.1 Fast.
- Grok 4.1 Fast is cheaper at $0.20 / $0.50 per million input/output tokens, against $0.26 / $0.38 for DeepSeek-V3.2-Exp.
- DeepSeek-V3.2-Exp accepts more context: 164K tokens versus 128K.
- DeepSeek-V3.2-Exp has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 44.3 | 41.4 |
| Rank | 78 | 136 |
| Context | 164K | 128K |
| Input $/M | $0.26 | $0.20 |
| Output $/M | $0.38 | $0.50 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.2-Exp: 46.5 (#65)
- Grok 4.1 Fast: 34.1 (#245)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena WebDev | 1362 | 1242 |
| LMArena Coding | 1454 | 1411 |
| SWE-bench Verified (bash only) | 70% | — |
| Aider Polyglot | 74.2% | — |
| SWE-bench Multilingual | 59% | — |
| SciCode | 38.9% | — |
| WeirdML | 39.5% | — |
| ALE-Bench | — | 394.93 |

## Agentic & Tool Use

- DeepSeek-V3.2-Exp: 32.7 (#59)
- Grok 4.1 Fast: 36.3 (#39)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| Berkeley Function Calling Leaderboard | 56.7% | 69.6% |
| Vending-Bench 2 | 1,034 | 1,107 |
| Terminal-Bench | 39.6% | — |
| APEX-Agents | 21.3% | — |
| TheAgentCompany | 42.9% | — |
| τ²-bench Banking | — | 13.1% |
| LMArena Search | — | 1171 |

## Reasoning

- DeepSeek-V3.2-Exp: 22.1 (#208)
- Grok 4.1 Fast: 43.4 (#49)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| NYT Connections (extended) | 36.7% | 87.4% |
| LMArena Hard Prompts | 1434 | 1407 |
| DTBench | 87.7% | 87.7% |
| ARC-AGI-2 | 4% | — |
| SimpleBench | — | 56% |
| Kagi LLM Benchmark | 52.2% | — |
| ARC-AGI-1 | 57% | — |
| CritPt | 2.9% | — |
| Chess Puzzles | 14% | — |
| Thematic Generalization | 65% | — |
| LMCA | 29.1% | — |
| Epoch Capabilities Index | 146.27 | — |
| ForecastBench | — | 61 |

## Math

- DeepSeek-V3.2-Exp: 41.7 (#87)
- Grok 4.1 Fast: 31.9 (#221)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| MathArena Final-Answer Competitions | 57.7% | 60.9% |
| ProofBench | 8% | 4% |
| LMArena Math | 1435 | 1408 |
| OTIS Mock AIME 2024-2025 | 87.8% | — |
| FrontierMath (Feb 2025 set) | 22.1% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- DeepSeek-V3.2-Exp: 51.7 (#66)
- Grok 4.1 Fast: 33.1 (#207)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| Vectara Hallucination Rate | 5.3% | 17.8% |
| LMArena Expert | 1436 | 1399 |
| GPQA Diamond | 83.4% | — |

## Multimodal

- DeepSeek-V3.2-Exp: —
- Grok 4.1 Fast: 37.0 (#76)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Vision | — | 1201 |

## Multilingual

- DeepSeek-V3.2-Exp: 52.2 (#90)
- Grok 4.1 Fast: 51.0 (#114)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Non-English | 1409 | 1391 |
| LMArena Chinese | 1461 | 1441 |
| LMArena French | 1433 | 1415 |
| LMArena German | 1440 | 1404 |
| LMArena Japanese | 1374 | 1349 |
| LMArena Korean | 1371 | 1361 |
| LMArena Russian | 1424 | 1387 |
| LMArena Spanish | 1440 | 1413 |

## Instruction Following

- DeepSeek-V3.2-Exp: 74.5 (#93)
- Grok 4.1 Fast: 72.7 (#133)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Instruction Following | 1413 | 1376 |

## Long Context

- DeepSeek-V3.2-Exp: 47.6 (#16)
- Grok 4.1 Fast: 42.4 (#126)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Longer Query | 1428 | 1390 |
| Fiction.LiveBench | 83.3% | — |
| CL-bench | 13.2% | — |
| CL-bench Life | 9.5% | — |

## Writing & Preference

- DeepSeek-V3.2-Exp: 62.4 (#77)
- Grok 4.1 Fast: 57.2 (#131)

| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Text | 1425 | 1408 |
| LMArena Creative Writing | 1403 | 1394 |
| EQ-Bench Creative Writing | 1515 | 1327 |
| LMArena Multi-Turn | 1427 | 1389 |

## FAQ

### Is DeepSeek-V3.2-Exp better than Grok 4.1 Fast?

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 41.4 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.2-Exp or Grok 4.1 Fast?

Grok 4.1 Fast is cheaper. It lists at $0.20 per million input tokens and $0.50 per million output tokens; DeepSeek-V3.2-Exp lists at $0.26 and $0.38.

### Is DeepSeek-V3.2-Exp or Grok 4.1 Fast better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 34.1 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3.2-Exp does, with 164K tokens against 128K.

### How many benchmarks do DeepSeek-V3.2-Exp and Grok 4.1 Fast share?

26 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 49 scored results on Noometry and Grok 4.1 Fast has 32.