# DeepSeek-V3.2-Exp vs Inkling

> DeepSeek-V3.2-Exp and Inkling score almost the same on the Noometry Index (44.3 vs 44.1), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-exp-vs-inkling
- Last updated: 2026-10-10
- Shared benchmarks: 32

## Summary

- They share 32 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 4 categories and Inkling in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Inkling leads 40.4 to 22.1.
- The biggest single-benchmark swing is ARC-AGI-2: 4% for DeepSeek-V3.2-Exp and 36.5% for Inkling.
- DeepSeek-V3.2-Exp is cheaper at $0.26 / $0.38 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- DeepSeek-V3.2-Exp accepts more context: 164K tokens versus 66K.

## Snapshot

| | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| Provider | DeepSeek | Thinking Machines Lab |
| Noometry Index | 44.3 | 44.1 |
| Rank | 78 | 80 |
| Context | 164K | 66K |
| Input $/M | $0.26 | $1.87 |
| Output $/M | $0.38 | $4.68 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.2-Exp: 46.5 (#65)
- Inkling: 34.5 (#234)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| LMArena WebDev | 1362 | 1413 |
| SciCode | 38.9% | 47% |
| WeirdML | 39.5% | 32.3% |
| LMArena Coding | 1454 | 1464 |
| FrontierCode | — | 14% |
| SWE-bench Verified (bash only) | 70% | — |
| Aider Polyglot | 74.2% | — |
| SWE-bench Multilingual | 59% | — |
| FrontierSWE | — | 4.1% |
| ALE-Bench | — | 946 |

## Agentic & Tool Use

- DeepSeek-V3.2-Exp: 32.7 (#59)
- Inkling: 29.6 (#85)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| APEX-Agents | 21.3% | 33.8% |
| Terminal-Bench | 39.6% | — |
| Berkeley Function Calling Leaderboard | 56.7% | — |
| TheAgentCompany | 42.9% | — |
| τ²-bench Banking | — | 25% |
| Vending-Bench 2 | 1,034 | — |

## Reasoning

- DeepSeek-V3.2-Exp: 22.1 (#208)
- Inkling: 40.4 (#56)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| ARC-AGI-2 | 4% | 36.5% |
| ARC-AGI-1 | 57% | 79.5% |
| CritPt | 2.9% | 5.4% |
| Chess Puzzles | 14% | 21% |
| LMArena Hard Prompts | 1434 | 1451 |
| DTBench | 87.7% | 87.5% |
| LMCA | 29.1% | 37.6% |
| Epoch Capabilities Index | 146.27 | 148.54 |
| SimpleBench | — | 50% |
| Kagi LLM Benchmark | 52.2% | — |
| NYT Connections (extended) | 36.7% | — |
| Thematic Generalization | 65% | — |

## Math

- DeepSeek-V3.2-Exp: 41.7 (#87)
- Inkling: 31.3 (#225)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 87.8% | 88.9% |
| ProofBench | 8% | 0% |
| LMArena Math | 1435 | 1479 |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| FrontierMath Tier 4 | — | 4.9% |
| MathArena Final-Answer Competitions | 57.7% | — |
| FrontierMath (Feb 2025 set) | 22.1% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- DeepSeek-V3.2-Exp: 51.7 (#66)
- Inkling: 55.1 (#49)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| GPQA Diamond | 83.4% | 88.3% |
| LMArena Expert | 1436 | 1465 |
| SimpleQA Verified | — | 40.3% |
| Vectara Hallucination Rate | 5.3% | — |

## Multilingual

- DeepSeek-V3.2-Exp: 52.2 (#90)
- Inkling: 54.0 (#52)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| LMArena Non-English | 1409 | 1434 |
| LMArena Chinese | 1461 | 1490 |
| LMArena French | 1433 | 1458 |
| LMArena German | 1440 | 1446 |
| LMArena Japanese | 1374 | 1429 |
| LMArena Korean | 1371 | 1404 |
| LMArena Russian | 1424 | 1429 |
| LMArena Spanish | 1440 | 1448 |

## Instruction Following

- DeepSeek-V3.2-Exp: 74.5 (#93)
- Inkling: 75.1 (#71)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| LMArena Instruction Following | 1413 | 1426 |

## Long Context

- DeepSeek-V3.2-Exp: 47.6 (#16)
- Inkling: 43.8 (#86)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| LMArena Longer Query | 1428 | 1434 |
| Fiction.LiveBench | 83.3% | — |
| CL-bench | 13.2% | — |
| CL-bench Life | 9.5% | — |

## Writing & Preference

- DeepSeek-V3.2-Exp: 62.4 (#77)
- Inkling: 65.2 (#51)

| Benchmark | DeepSeek-V3.2-Exp | Inkling |
|---|---|---|
| LMArena Text | 1425 | 1441 |
| LMArena Creative Writing | 1403 | 1387 |
| EQ-Bench Creative Writing | 1515 | 1611 |
| LMArena Multi-Turn | 1427 | 1436 |
| EQ-Bench 4 | — | 1226 |

## FAQ

### Is DeepSeek-V3.2-Exp better than Inkling?

DeepSeek-V3.2-Exp and Inkling score almost the same on the Noometry Index (44.3 vs 44.1), so choose on price, context window or the category you care about most.

### Which is cheaper, DeepSeek-V3.2-Exp or Inkling?

DeepSeek-V3.2-Exp is cheaper. It lists at $0.26 per million input tokens and $0.38 per million output tokens; Inkling lists at $1.87 and $4.68.

### Is DeepSeek-V3.2-Exp or Inkling better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 34.5 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3.2-Exp does, with 164K tokens against 66K.

### How many benchmarks do DeepSeek-V3.2-Exp and Inkling share?

32 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 49 scored results on Noometry and Inkling has 41.