# Inkling vs Qwen3.5 122B-A10B

> Inkling is the stronger model overall, scoring 44.1 to 42.1 on the Noometry Index. Qwen3.5 122B-A10B costs 2.3× less per token, which makes it the better buy when Inkling's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/inkling-vs-qwen3-5-122b-a10b
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Inkling scores higher in 6 categories and Qwen3.5 122B-A10B in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Inkling leads 55.1 to 38.8.
- The biggest single-benchmark swing is SciCode: 47% for Inkling and 35.6% for Qwen3.5 122B-A10B.
- Qwen3.5 122B-A10B is cheaper at $0.40 / $3.20 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- Qwen3.5 122B-A10B accepts more context: 262K tokens versus 66K.

## Snapshot

| | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| Provider | Thinking Machines Lab | Alibaba (Qwen) |
| Noometry Index | 44.1 | 42.1 |
| Rank | 80 | 119 |
| Context | 66K | 262K |
| Input $/M | $1.87 | $0.40 |
| Output $/M | $4.68 | $3.20 |
| Weights | Open | Open |

## Coding

- Inkling: 34.5 (#234)
- Qwen3.5 122B-A10B: 39.1 (#162)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena WebDev | 1413 | 1360 |
| SciCode | 47% | 35.6% |
| LMArena Coding | 1464 | 1436 |
| FrontierCode | 14% | — |
| FrontierSWE | 4.1% | — |
| WeirdML | 32.3% | — |
| ALE-Bench | 946 | — |

## Agentic & Tool Use

- Inkling: 29.6 (#85)
- Qwen3.5 122B-A10B: —

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| APEX-Agents | 33.8% | — |
| τ²-bench Banking | 25% | — |

## Reasoning

- Inkling: 40.4 (#56)
- Qwen3.5 122B-A10B: 27.2 (#123)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| CritPt | 5.4% | 0.9% |
| LMArena Hard Prompts | 1451 | 1421 |
| DTBench | 87.5% | 84.3% |
| LMCA | 37.6% | 32.2% |
| ARC-AGI-2 | 36.5% | — |
| SimpleBench | 50% | — |
| NYT Connections (extended) | — | 51.7% |
| ARC-AGI-1 | 79.5% | — |
| Chess Puzzles | 21% | — |
| Thematic Generalization | — | 51.2% |
| Mystery Game Puzzles | — | 17% |
| Epoch Capabilities Index | 148.54 | — |

## Math

- Inkling: 31.3 (#225)
- Qwen3.5 122B-A10B: 39.1 (#112)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Math | 1479 | 1432 |
| FrontierMath (Tiers 1-3) | 33.3% | — |
| FrontierMath Tier 4 | 4.9% | — |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | 0% | — |

## Knowledge

- Inkling: 55.1 (#49)
- Qwen3.5 122B-A10B: 38.8 (#142)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Expert | 1465 | 1432 |
| GPQA Diamond | 88.3% | — |
| SimpleQA Verified | 40.3% | — |
| Vectara Hallucination Rate | — | 11.2% |

## Multimodal

- Inkling: —
- Qwen3.5 122B-A10B: 39.6 (#57)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Vision | — | 1245 |

## Multilingual

- Inkling: 54.0 (#52)
- Qwen3.5 122B-A10B: 51.6 (#107)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Non-English | 1434 | 1400 |
| LMArena Chinese | 1490 | 1462 |
| LMArena French | 1458 | 1442 |
| LMArena German | 1446 | 1426 |
| LMArena Japanese | 1429 | 1367 |
| LMArena Korean | 1404 | 1352 |
| LMArena Russian | 1429 | 1400 |
| LMArena Spanish | 1448 | 1424 |

## Instruction Following

- Inkling: 75.1 (#71)
- Qwen3.5 122B-A10B: 73.8 (#115)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Instruction Following | 1426 | 1399 |

## Long Context

- Inkling: 43.8 (#86)
- Qwen3.5 122B-A10B: 43.0 (#109)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Longer Query | 1434 | 1410 |

## Writing & Preference

- Inkling: 65.2 (#51)
- Qwen3.5 122B-A10B: 60.0 (#105)

| Benchmark | Inkling | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Text | 1441 | 1417 |
| LMArena Creative Writing | 1387 | 1368 |
| LMArena Multi-Turn | 1436 | 1416 |
| EQ-Bench Creative Writing | 1611 | — |
| EQ-Bench 4 | 1226 | — |

## FAQ

### Is Inkling better than Qwen3.5 122B-A10B?

Inkling is the stronger model overall, scoring 44.1 to 42.1 on the Noometry Index. Qwen3.5 122B-A10B costs 2.3× less per token, which makes it the better buy when Inkling's lead doesn't matter for your workload.

### Which is cheaper, Inkling or Qwen3.5 122B-A10B?

Qwen3.5 122B-A10B is cheaper. It lists at $0.40 per million input tokens and $3.20 per million output tokens; Inkling lists at $1.87 and $4.68.

### Is Inkling or Qwen3.5 122B-A10B better for coding?

Qwen3.5 122B-A10B scores higher on coding benchmarks: 39.1 versus 34.5 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5 122B-A10B does, with 262K tokens against 66K.

### How many benchmarks do Inkling and Qwen3.5 122B-A10B share?

22 benchmarks have published results for both models. Inkling has 41 scored results on Noometry and Qwen3.5 122B-A10B has 27.