# Inkling vs Qwen2.5 7B Instruct

> Inkling is the stronger model overall, scoring 44.1 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 8.4× 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-qwen2-5-7b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 6

## Summary

- They share 6 benchmarks with published results for both. Inkling scores higher in 6 categories and Qwen2.5 7B Instruct in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Inkling leads 55.1 to 17.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 88.9% for Inkling and 2.5% for Qwen2.5 7B Instruct.
- Qwen2.5 7B Instruct is cheaper at $0.17 / $0.70 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- Qwen2.5 7B Instruct accepts more context: 131K tokens versus 66K.

## Snapshot

| | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | Thinking Machines Lab | Alibaba (Qwen) |
| Noometry Index | 44.1 | 29.0 |
| Rank | 80 | 320 |
| Context | 66K | 131K |
| Input $/M | $1.87 | $0.17 |
| Output $/M | $4.68 | $0.70 |
| Weights | Open | Open |

## Coding

- Inkling: 34.5 (#234)
- Qwen2.5 7B Instruct: 36.5 (#208)

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| FrontierCode | 14% | — |
| LMArena WebDev | 1413 | — |
| FrontierSWE | 4.1% | — |
| SciCode | 47% | — |
| WeirdML | 32.3% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1464 | — |
| BigCodeBench Complete | — | 46.1% |
| ALE-Bench | 946 | — |

## Agentic & Tool Use

- Inkling: 29.6 (#85)
- Qwen2.5 7B Instruct: 23.8 (#124)

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| APEX-Agents | 33.8% | — |
| τ²-bench Banking | 25% | — |
| BALROG | — | 7.8% |

## Reasoning

- Inkling: 40.4 (#56)
- Qwen2.5 7B Instruct: 14.8 (#322)

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| Chess Puzzles | 21% | 0% |
| DTBench | 87.5% | 47.7% |
| LMCA | 37.6% | 6.4% |
| Epoch Capabilities Index | 148.54 | 118.51 |
| ARC-AGI-2 | 36.5% | — |
| SimpleBench | 50% | — |
| ARC-AGI-1 | 79.5% | — |
| CritPt | 5.4% | — |
| LMArena Hard Prompts | 1451 | — |

## Math

- Inkling: 31.3 (#225)
- Qwen2.5 7B Instruct: 12.6 (#306)

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | 2.5% |
| FrontierMath (Tiers 1-3) | 33.3% | — |
| FrontierMath Tier 4 | 4.9% | — |
| ProofBench | 0% | — |
| Omni-MATH | — | 29.4% |
| LMArena Math | 1479 | — |

## Knowledge

- Inkling: 55.1 (#49)
- Qwen2.5 7B Instruct: 17.0 (#286)

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 88.3% | 35.5% |
| SimpleQA Verified | 40.3% | — |
| MMLU-Pro | — | 53.9% |
| GPQA (HELM) | — | 34.1% |
| LMArena Expert | 1465 | — |
| MMLU | — | 72.9% |

## Multilingual

- Inkling: 54.0 (#52)
- Qwen2.5 7B Instruct: —

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1434 | — |
| LMArena Chinese | 1490 | — |
| LMArena French | 1458 | — |
| LMArena German | 1446 | — |
| LMArena Japanese | 1429 | — |
| LMArena Korean | 1404 | — |
| LMArena Russian | 1429 | — |
| LMArena Spanish | 1448 | — |

## Instruction Following

- Inkling: 75.1 (#71)
- Qwen2.5 7B Instruct: 63.2 (#231)

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1426 | — |

## Long Context

- Inkling: 43.8 (#86)
- Qwen2.5 7B Instruct: —

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1434 | — |

## Writing & Preference

- Inkling: 65.2 (#51)
- Qwen2.5 7B Instruct: 48.8 (#195)

| Benchmark | Inkling | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1441 | — |
| LMArena Creative Writing | 1387 | — |
| EQ-Bench Creative Writing | 1611 | — |
| WildBench | — | 73.1% |
| EQ-Bench 4 | 1226 | — |
| LMArena Multi-Turn | 1436 | — |

## FAQ

### Is Inkling better than Qwen2.5 7B Instruct?

Inkling is the stronger model overall, scoring 44.1 to 29.0 on the Noometry Index. Qwen2.5 7B Instruct costs 8.4× less per token, which makes it the better buy when Inkling's lead doesn't matter for your workload.

### Which is cheaper, Inkling or Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is cheaper. It lists at $0.17 per million input tokens and $0.70 per million output tokens; Inkling lists at $1.87 and $4.68.

### Is Inkling or Qwen2.5 7B Instruct better for coding?

Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 34.5 in the Noometry coding category.

### Which has the bigger context window?

Qwen2.5 7B Instruct does, with 131K tokens against 66K.

### How many benchmarks do Inkling and Qwen2.5 7B Instruct share?

6 benchmarks have published results for both models. Inkling has 41 scored results on Noometry and Qwen2.5 7B Instruct has 15.