# Gemini 3.8 Flash vs Qwen2.5-Coder-32B

> Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 2.0× less per token, which makes it the better buy when Gemini 3.8 Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-8-flash-vs-qwen2-5-coder-32b
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Gemini 3.8 Flash scores higher in 8 categories and Qwen2.5-Coder-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.8 Flash leads 76.9 to 21.2.
- Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.8 Flash.
- Gemini 3.8 Flash accepts more context: 1.05M tokens versus 33K.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| Provider | Google | Alibaba (Qwen) |
| Noometry Index | 61.8 | 33.4 |
| Rank | 11 | 245 |
| Context | 1.05M | 33K |
| Input $/M | $0.75 | $0.66 |
| Output $/M | $3.75 | $1 |
| Weights | Proprietary | Open |

## Coding

- Gemini 3.8 Flash: 59.2 (#15)
- Qwen2.5-Coder-32B: 22.6 (#333)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Coding | 1510 | 1276 |
| DeepSWE | 73.8% | — |
| FrontierCode | 41.2% | — |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| CursorBench | 39.6% | — |
| LMArena WebDev | 1584 | — |
| FrontierSWE | 19.6% | — |
| SciCode | 56.6% | — |
| WeirdML | 84.8% | — |
| BigCodeBench Instruct | — | 49% |
| LiveBench Coding | — | 56.9% |
| BigCodeBench Complete | — | 58% |
| ALE-Bench | 1,270 | — |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |

## Agentic & Tool Use

- Gemini 3.8 Flash: 41.8 (#21)
- Qwen2.5-Coder-32B: —

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| APEX-Agents | 64.3% | — |
| Remote Labor Index | 5.8% | — |
| GDP.pdf | 23.4% | — |
| Vending-Bench 2 | 5,094 | — |

## Reasoning

- Gemini 3.8 Flash: 76.9 (#5)
- Qwen2.5-Coder-32B: 21.2 (#225)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Hard Prompts | 1508 | 1251 |
| Epoch Capabilities Index | 156.71 | 119.49 |
| ARC-AGI-2 | 89.2% | — |
| NYT Connections (extended) | 97.4% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 18.3% | — |
| Chess Puzzles | 61% | — |
| LiveBench Reasoning | — | 42.1% |
| Mystery Game Puzzles | 47% | — |
| DTBench | 95.7% | — |
| LiveBench Data Analysis | — | 49.9% |
| LMCA | 52.9% | — |
| Surface Evolver Bench | 76.9% | — |
| HellaSwag | — | 83% |
| LiveBench | — | 46.2% |
| WinoGrande | — | 80.8% |

## Math

- Gemini 3.8 Flash: 65.3 (#28)
- Qwen2.5-Coder-32B: 33.3 (#204)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Math | 1528 | 1251 |
| FrontierMath (Tiers 1-3) | 68.4% | — |
| FrontierMath Tier 4 | 22% | — |
| OTIS Mock AIME 2024-2025 | 98.9% | — |
| ProofBench | 48% | — |
| LiveBench Math | — | 46.6% |
| GSM8K | — | 93% |

## Knowledge

- Gemini 3.8 Flash: 74.8 (#2)
- Qwen2.5-Coder-32B: 33.4 (#203)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1524 | 1221 |
| GPQA Diamond | 95.4% | — |
| Humanity's Last Exam | 44.5% | — |
| SimpleQA Verified | 69.7% | — |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |

## Multimodal

- Gemini 3.8 Flash: 40.7 (#45)
- Qwen2.5-Coder-32B: —

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1314 | — |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 31.7% | — |

## Multilingual

- Gemini 3.8 Flash: 58.0 (#5)
- Qwen2.5-Coder-32B: 37.8 (#235)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1491 | 1205 |
| LMArena Chinese | 1554 | 1222 |
| LMArena Russian | 1515 | 1228 |
| LMArena French | 1498 | — |
| LMArena German | 1493 | — |
| LMArena Japanese | 1502 | — |
| LMArena Korean | 1459 | — |
| LMArena Spanish | 1485 | — |

## Instruction Following

- Gemini 3.8 Flash: 78.0 (#13)
- Qwen2.5-Coder-32B: 61.4 (#245)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Instruction Following | 1490 | 1223 |
| LiveBench Instruction Following | — | 58.7% |

## Long Context

- Gemini 3.8 Flash: 46.3 (#24)
- Qwen2.5-Coder-32B: 38.0 (#208)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1508 | 1251 |

## Writing & Preference

- Gemini 3.8 Flash: 72.2 (#15)
- Qwen2.5-Coder-32B: 41.6 (#240)

| Benchmark | Gemini 3.8 Flash | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1499 | 1230 |
| LMArena Creative Writing | 1492 | 1174 |
| LMArena Multi-Turn | 1501 | 1222 |
| EQ-Bench Creative Writing | 1748 | — |
| LiveBench Language | — | 23.3% |

## FAQ

### Is Gemini 3.8 Flash better than Qwen2.5-Coder-32B?

Gemini 3.8 Flash is the stronger model overall, scoring 61.8 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 2.0× less per token, which makes it the better buy when Gemini 3.8 Flash's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.8 Flash or Qwen2.5-Coder-32B?

Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; Gemini 3.8 Flash lists at $0.75 and $3.75.

### Is Gemini 3.8 Flash or Qwen2.5-Coder-32B better for coding?

Gemini 3.8 Flash scores higher on coding benchmarks: 59.2 versus 22.6 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.8 Flash does, with 1.05M tokens against 33K.

### How many benchmarks do Gemini 3.8 Flash and Qwen2.5-Coder-32B share?

13 benchmarks have published results for both models. Gemini 3.8 Flash has 50 scored results on Noometry and Qwen2.5-Coder-32B has 31.