Model comparison
DeepSeek-V3.2-Exp vs Grok 4.1 Fast
DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.9 to 40.9 on the Noometry Index.
Last verified . 26 shared benchmarks.
DeepSeekSummary
- They share 26 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 8 categories and Grok 4.1 Fast in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.1 Fast leads 42.3 to 22.0.
- 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.
Side by side
| DeepSeek-V3.2-Exp | Grok 4.1 Fast | |
|---|---|---|
| Provider | DeepSeek | xAI |
| Noometry Index | 44.9 | 40.9 |
| Released | 2025-09-29 | 2025-06-27 |
| Weights | Open | Proprietary |
| Context window | 164K | 128K |
| Max output | 66K | 30K |
| Input $ / M tokens | $0.26 | $0.20 |
| Output $ / M tokens | $0.38 | $0.50 |
| Results tracked | 48 | 32 |
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Category by category
Coding DeepSeek-V3.2-Exp leads
DeepSeek-V3.2-Exp: 46.4 (#61), Grok 4.1 Fast: 33.8 (#236)
| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena WebDev | 1362 | 1241 |
| 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 leads
DeepSeek-V3.2-Exp: 37.9 (#31), Grok 4.1 Fast: 36.1 (#35)
| 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% | — |
| TheAgentCompany | 42.9% | — |
| τ²-bench Banking | — | 13.1% |
| LMArena Search | — | 1171 |
Reasoning Grok 4.1 Fast leads
DeepSeek-V3.2-Exp: 22.0 (#185), Grok 4.1 Fast: 42.3 (#45)
| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| NYT Connections (extended) | 36.7% | 87.4% |
| LMArena Hard Prompts | 1433 | 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 | 146.28 | — |
| ForecastBench | — | 61 |
Math DeepSeek-V3.2-Exp leads
DeepSeek-V3.2-Exp: 40.8 (#75), Grok 4.1 Fast: 30.9 (#201)
| 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 leads
DeepSeek-V3.2-Exp: 51.6 (#61), Grok 4.1 Fast: 32.6 (#203)
| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| Vectara Hallucination Rate | 5.3% | 17.8% |
| LMArena Expert | 1436 | 1398 |
| GPQA Diamond | 83.4% | — |
Multimodal Not comparable
DeepSeek-V3.2-Exp: —, Grok 4.1 Fast: 36.3 (#71)
| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Vision | — | 1201 |
Multilingual DeepSeek-V3.2-Exp leads
DeepSeek-V3.2-Exp: 52.4 (#85), Grok 4.1 Fast: 51.1 (#110)
| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Non-English | 1409 | 1391 |
| LMArena Chinese | 1461 | 1441 |
| LMArena French | 1435 | 1416 |
| LMArena German | 1440 | 1404 |
| LMArena Japanese | 1377 | 1347 |
| LMArena Korean | 1372 | 1361 |
| LMArena Russian | 1423 | 1387 |
| LMArena Spanish | 1441 | 1411 |
Instruction Following DeepSeek-V3.2-Exp leads
DeepSeek-V3.2-Exp: 74.7 (#89), Grok 4.1 Fast: 72.8 (#127)
| Benchmark | DeepSeek-V3.2-Exp | Grok 4.1 Fast |
|---|---|---|
| LMArena Instruction Following | 1413 | 1376 |
Long Context DeepSeek-V3.2-Exp leads
DeepSeek-V3.2-Exp: 47.6 (#15), Grok 4.1 Fast: 42.4 (#121)
| 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 leads
DeepSeek-V3.2-Exp: 62.5 (#73), Grok 4.1 Fast: 57.4 (#126)
| 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 |
Frequently asked questions
Is DeepSeek-V3.2-Exp better than Grok 4.1 Fast?
DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.9 to 40.9 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: 46.4 versus 33.8 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 48 scored results on Noometry and Grok 4.1 Fast has 32.