# Gemini 2.5 Flash vs Qwen3.8 27B

> Qwen3.8 27B is the stronger model overall, scoring 46.0 to 39.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-2-5-flash-vs-qwen3-8-27b
- Last updated: 2026-10-12
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 3 categories and Qwen3.8 27B in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.8 27B leads 41.0 to 18.1.
- The biggest single-benchmark swing is ARC-AGI-1: 33.3% for Gemini 2.5 Flash and 87.5% for Qwen3.8 27B.
- Qwen3.8 27B is cheaper at $0.04 / $2.30 per million input/output tokens, against $0.30 / $2.50 for Gemini 2.5 Flash.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 262K.
- Qwen3.8 27B has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| Provider | Google | Alibaba (Qwen) |
| Noometry Index | 39.3 | 46.0 |
| Rank | 170 | 68 |
| Context | 1.05M | 262K |
| Input $/M | $0.30 | $0.04 |
| Output $/M | $2.50 | $2.30 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.5 Flash: 35.8 (#220)
- Qwen3.8 27B: 50.5 (#44)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Coding | 1424 | 1482 |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1593 |
| SciCode | — | 46.6% |
| WeirdML | 41.9% | — |
| ALE-Bench | 661.88 | — |

## Agentic & Tool Use

- Gemini 2.5 Flash: 30.8 (#74)
- Qwen3.8 27B: 32.9 (#57)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| Terminal-Bench | 17.1% | — |
| APEX-Agents | — | 47.5% |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |

## Reasoning

- Gemini 2.5 Flash: 18.1 (#286)
- Qwen3.8 27B: 41.0 (#54)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| ARC-AGI-2 | 2.5% | 42.4% |
| ARC-AGI-1 | 33.3% | 87.5% |
| CritPt | 1.1% | 5.4% |
| LMArena Hard Prompts | 1422 | 1460 |
| DTBench | 76.5% | 88% |
| LMCA | 27.5% | 41.4% |
| Epoch Capabilities Index | 143.03 | 149.38 |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| NYT Connections (extended) | — | 54.5% |
| EnigmaEval | 2.7% | — |
| Surface Evolver Bench | — | 45% |
| ForecastBench | 60.6 | — |

## Math

- Gemini 2.5 Flash: 39.9 (#98)
- Qwen3.8 27B: 37.1 (#161)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Math | 1415 | 1456 |
| OTIS Mock AIME 2024-2025 | 73.1% | — |
| ProofBench | — | 16% |
| Omni-MATH | 38.5% | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Gemini 2.5 Flash: 36.4 (#168)
- Qwen3.8 27B: 41.6 (#109)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Expert | 1426 | 1482 |
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| Confabulations | 16.8% | — |
| Vectara Hallucination Rate | 7.8% | — |
| GPQA (HELM) | 39% | — |

## Multimodal

- Gemini 2.5 Flash: 41.8 (#32)
- Qwen3.8 27B: 41.3 (#37)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Vision | 1253 | 1271 |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |

## Multilingual

- Gemini 2.5 Flash: 52.3 (#88)
- Qwen3.8 27B: 53.7 (#60)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Non-English | 1409 | 1430 |
| LMArena Chinese | 1450 | 1504 |
| LMArena French | 1433 | 1465 |
| LMArena German | 1418 | 1438 |
| LMArena Japanese | 1405 | 1384 |
| LMArena Korean | 1385 | 1393 |
| LMArena Russian | 1415 | 1415 |
| LMArena Spanish | 1421 | 1448 |

## Instruction Following

- Gemini 2.5 Flash: 75.7 (#54)
- Qwen3.8 27B: 75.8 (#53)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Instruction Following | 1405 | 1439 |
| IFEval | 89.8% | — |

## Long Context

- Gemini 2.5 Flash: 47.5 (#17)
- Qwen3.8 27B: 44.3 (#70)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Longer Query | 1419 | 1450 |
| Fiction.LiveBench | 77.8% | — |

## Writing & Preference

- Gemini 2.5 Flash: 53.8 (#157)
- Qwen3.8 27B: 65.8 (#43)

| Benchmark | Gemini 2.5 Flash | Qwen3.8 27B |
|---|---|---|
| LMArena Text | 1417 | 1441 |
| LMArena Creative Writing | 1400 | 1384 |
| EQ-Bench Creative Writing | 1137 | 1671 |
| LMArena Multi-Turn | 1408 | 1441 |
| Short-Story Creative Writing | 76.5% | — |
| WildBench | 81.7% | — |

## FAQ

### Is Gemini 2.5 Flash better than Qwen3.8 27B?

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 39.3 on the Noometry Index.

### Which is cheaper, Gemini 2.5 Flash or Qwen3.8 27B?

Qwen3.8 27B is cheaper. It lists at $0.04 per million input tokens and $2.30 per million output tokens; Gemini 2.5 Flash lists at $0.30 and $2.50.

### Is Gemini 2.5 Flash or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 35.8 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Flash does, with 1.05M tokens against 262K.

### How many benchmarks do Gemini 2.5 Flash and Qwen3.8 27B share?

25 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and Qwen3.8 27B has 31.