# Inkling vs Qwen3.5 27B

> Inkling is the stronger model overall, scoring 44.1 to 41.4 on the Noometry Index. Qwen3.5 27B costs 3.1× 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-qwen3-5-27b
- 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 27B in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Inkling leads 55.2 to 37.4.
- The biggest single-benchmark swing is WeirdML: 32.3% for Inkling and 39.5% for Qwen3.5 27B.
- Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- Qwen3.5 27B accepts more context: 262K tokens versus 66K.

## Snapshot

| | Inkling | Qwen3.5 27B |
|---|---|---|
| Provider | Thinking Machines Lab | Alibaba (Qwen) |
| Noometry Index | 44.1 | 41.4 |
| Rank | 75 | 127 |
| Context | 66K | 262K |
| Input $/M | $1.87 | $0.30 |
| Output $/M | $4.68 | $2.40 |
| Weights | Open | Open |

## Coding

- Inkling: 34.1 (#229)
- Qwen3.5 27B: 38.6 (#159)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena WebDev | 1412 | 1357 |
| WeirdML | 32.3% | 39.5% |
| LMArena Coding | 1463 | 1427 |
| ALE-Bench | 946 | 349.45 |
| FrontierCode | 14% | — |
| FrontierSWE | 4.1% | — |
| SciCode | 47% | — |

## Agentic & Tool Use

- Inkling: 29.5 (#76)
- Qwen3.5 27B: —

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| APEX-Agents | 33.8% | — |
| τ²-bench Banking | 25% | — |
| Vending-Bench 2 | — | 201.98 |

## Reasoning

- Inkling: 40.6 (#48)
- Qwen3.5 27B: 26.6 (#116)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1452 | 1414 |
| DTBench | 87.5% | 82.4% |
| LMCA | 37.6% | 34% |
| ARC-AGI-2 | 36.5% | — |
| SimpleBench | 50% | — |
| NYT Connections (extended) | — | 47.9% |
| ARC-AGI-1 | 79.5% | — |
| CritPt | 5.4% | — |
| Chess Puzzles | 21% | — |
| Thematic Generalization | — | 45.5% |
| Epoch Capabilities Index | 148.6 | — |

## Math

- Inkling: 31.2 (#198)
- Qwen3.5 27B: 36.8 (#103)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1482 | 1428 |
| FrontierMath (Tiers 1-3) | 33.3% | — |
| FrontierMath Tier 4 | 4.9% | — |
| MathArena Final-Answer Competitions | — | 56.7% |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | 0% | — |

## Knowledge

- Inkling: 55.2 (#44)
- Qwen3.5 27B: 37.4 (#149)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Expert | 1468 | 1428 |
| GPQA Diamond | 88.3% | — |
| SimpleQA Verified | 40.3% | — |
| Vectara Hallucination Rate | — | 12.1% |

## Multimodal

- Inkling: —
- Qwen3.5 27B: 38.7 (#56)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | — | 1240 |

## Multilingual

- Inkling: 54.2 (#49)
- Qwen3.5 27B: 51.0 (#112)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 1434 | 1390 |
| LMArena Chinese | 1495 | 1478 |
| LMArena French | 1453 | 1409 |
| LMArena German | 1456 | 1393 |
| LMArena Japanese | 1428 | 1345 |
| LMArena Korean | 1401 | 1359 |
| LMArena Russian | 1430 | 1389 |
| LMArena Spanish | 1442 | 1408 |

## Instruction Following

- Inkling: 75.3 (#65)
- Qwen3.5 27B: 73.7 (#114)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1427 | 1393 |

## Long Context

- Inkling: 43.9 (#79)
- Qwen3.5 27B: 43.1 (#103)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 1436 | 1413 |

## Writing & Preference

- Inkling: 65.5 (#48)
- Qwen3.5 27B: 59.5 (#106)

| Benchmark | Inkling | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1443 | 1409 |
| LMArena Creative Writing | 1390 | 1362 |
| LMArena Multi-Turn | 1436 | 1410 |
| EQ-Bench Creative Writing | 1611 | — |
| EQ-Bench 4 | 1226 | — |

## FAQ

### Is Inkling better than Qwen3.5 27B?

Inkling is the stronger model overall, scoring 44.1 to 41.4 on the Noometry Index. Qwen3.5 27B costs 3.1× 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 27B?

Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; Inkling lists at $1.87 and $4.68.

### Is Inkling or Qwen3.5 27B better for coding?

Qwen3.5 27B scores higher on coding benchmarks: 38.6 versus 34.1 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5 27B does, with 262K tokens against 66K.

### How many benchmarks do Inkling and Qwen3.5 27B share?

22 benchmarks have published results for both models. Inkling has 41 scored results on Noometry and Qwen3.5 27B has 28.