# Inkling vs Qwen3.5 397B-A17B

> Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 44.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/inkling-vs-qwen3-5-397b-a17b
- Last updated: 2026-10-12
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. Inkling scores higher in 5 categories and Qwen3.5 397B-A17B in 4 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.5 397B-A17B leads 46.1 to 31.3.
- The biggest single-benchmark swing is τ²-bench Banking: 25% for Inkling and 9.8% for Qwen3.5 397B-A17B.
- Qwen3.5 397B-A17B is cheaper at $0.60 / $3.60 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- Qwen3.5 397B-A17B accepts more context: 262K tokens versus 66K.

## Snapshot

| | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| Provider | Thinking Machines Lab | Alibaba (Qwen) |
| Noometry Index | 44.1 | 46.0 |
| Rank | 80 | 67 |
| Context | 66K | 262K |
| Input $/M | $1.87 | $0.60 |
| Output $/M | $4.68 | $3.60 |
| Weights | Open | Open |

## Coding

- Inkling: 34.5 (#234)
- Qwen3.5 397B-A17B: 42.0 (#114)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena WebDev | 1413 | 1400 |
| LMArena Coding | 1464 | 1465 |
| FrontierCode | 14% | — |
| FrontierSWE | 4.1% | — |
| SciCode | 47% | — |
| WeirdML | 32.3% | — |
| ALE-Bench | 946 | — |

## Agentic & Tool Use

- Inkling: 29.6 (#85)
- Qwen3.5 397B-A17B: 33.3 (#53)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| APEX-Agents | 33.8% | 24.9% |
| τ²-bench Banking | 25% | 9.8% |
| τ²-bench Airline | — | 81.5% |
| τ²-bench Retail | — | 84.4% |
| τ²-bench Telecom | — | 97.8% |

## Reasoning

- Inkling: 40.4 (#56)
- Qwen3.5 397B-A17B: 34.5 (#70)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| Chess Puzzles | 21% | 13% |
| LMArena Hard Prompts | 1451 | 1448 |
| DTBench | 87.5% | 87.5% |
| LMCA | 37.6% | 37.9% |
| Epoch Capabilities Index | 148.54 | 146.65 |
| ARC-AGI-2 | 36.5% | — |
| SimpleBench | 50% | — |
| Kagi LLM Benchmark | — | 73.7% |
| NYT Connections (extended) | — | 58.9% |
| ARC-AGI-1 | 79.5% | — |
| CritPt | 5.4% | — |
| Thematic Generalization | — | 65.1% |
| Mystery Game Puzzles | — | 18% |

## Math

- Inkling: 31.3 (#225)
- Qwen3.5 397B-A17B: 46.1 (#73)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 33.3% | 31.2% |
| OTIS Mock AIME 2024-2025 | 88.9% | 88.9% |
| LMArena Math | 1479 | 1454 |
| FrontierMath Tier 4 | 4.9% | — |
| ProofBench | 0% | — |

## Knowledge

- Inkling: 55.1 (#49)
- Qwen3.5 397B-A17B: 53.3 (#58)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| GPQA Diamond | 88.3% | 86.4% |
| LMArena Expert | 1465 | 1462 |
| SimpleQA Verified | 40.3% | — |

## Multimodal

- Inkling: —
- Qwen3.5 397B-A17B: 40.7 (#44)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Vision | — | 1263 |

## Multilingual

- Inkling: 54.0 (#52)
- Qwen3.5 397B-A17B: 53.7 (#59)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Non-English | 1434 | 1430 |
| LMArena Chinese | 1490 | 1500 |
| LMArena French | 1458 | 1461 |
| LMArena German | 1446 | 1447 |
| LMArena Japanese | 1429 | 1426 |
| LMArena Korean | 1404 | 1384 |
| LMArena Russian | 1429 | 1429 |
| LMArena Spanish | 1448 | 1441 |

## Instruction Following

- Inkling: 75.1 (#71)
- Qwen3.5 397B-A17B: 75.0 (#77)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Instruction Following | 1426 | 1424 |

## Long Context

- Inkling: 43.8 (#86)
- Qwen3.5 397B-A17B: 44.1 (#74)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Longer Query | 1434 | 1442 |

## Writing & Preference

- Inkling: 65.2 (#51)
- Qwen3.5 397B-A17B: 62.3 (#79)

| Benchmark | Inkling | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Text | 1441 | 1438 |
| LMArena Creative Writing | 1387 | 1401 |
| EQ-Bench Creative Writing | 1611 | 1478 |
| LMArena Multi-Turn | 1436 | 1446 |
| EQ-Bench 4 | 1226 | — |

## FAQ

### Is Inkling better than Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 44.1 on the Noometry Index.

### Which is cheaper, Inkling or Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; Inkling lists at $1.87 and $4.68.

### Is Inkling or Qwen3.5 397B-A17B better for coding?

Qwen3.5 397B-A17B scores higher on coding benchmarks: 42.0 versus 34.5 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5 397B-A17B does, with 262K tokens against 66K.

### How many benchmarks do Inkling and Qwen3.5 397B-A17B share?

28 benchmarks have published results for both models. Inkling has 41 scored results on Noometry and Qwen3.5 397B-A17B has 36.