# Gemini 2.5 Flash-Lite vs Qwen3.7 Max

> Qwen3.7 Max is the stronger model overall, scoring 51.4 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 21× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-2-5-flash-lite-vs-qwen3-7-max
- Last updated: 2026-10-10
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 1 category and Qwen3.7 Max in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.7 Max leads 61.7 to 32.1.
- The biggest single-benchmark swing is DTBench: 62.8% for Gemini 2.5 Flash-Lite and 92.3% for Qwen3.7 Max.
- Gemini 2.5 Flash-Lite is cheaper at $0.10 / $0.40 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 1M.

## Snapshot

| | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| Provider | Google | Alibaba (Qwen) |
| Noometry Index | 36.4 | 51.4 |
| Rank | 208 | 35 |
| Context | 1.05M | 1M |
| Input $/M | $0.10 | $2.50 |
| Output $/M | $0.40 | $7.50 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 2.5 Flash-Lite: 38.0 (#167)
- Qwen3.7 Max: 50.2 (#43)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Coding | 1373 | 1498 |
| ALE-Bench | 325.9 | 1,189 |
| SWE-bench Verified | — | 77.3% |
| LMArena WebDev | — | 1515 |
| SciCode | — | 48.8% |
| WeirdML | 35.2% | — |

## Agentic & Tool Use

- Gemini 2.5 Flash-Lite: 27.8 (#89)
- Qwen3.7 Max: 21.8 (#129)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| Berkeley Function Calling Leaderboard | 36.9% | — |
| GBAEval | — | 0.4% |

## Reasoning

- Gemini 2.5 Flash-Lite: 21.5 (#196)
- Qwen3.7 Max: 48.4 (#36)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Hard Prompts | 1377 | 1483 |
| DTBench | 62.8% | 92.3% |
| LMCA | 18.1% | 44% |
| Epoch Capabilities Index | 133.93 | 153.74 |
| SimpleBench | — | 70.4% |
| Kagi LLM Benchmark | 40.5% | — |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 13.4% |
| Chess Puzzles | — | 19% |
| EBR-Bench | — | 9.5% |
| Mystery Game Puzzles | — | 32% |

## Math

- Gemini 2.5 Flash-Lite: 35.5 (#144)
- Qwen3.7 Max: 62.3 (#26)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Math | 1373 | 1488 |
| FrontierMath (Tiers 1-3) | — | 64.6% |
| FrontierMath Tier 4 | — | 34.1% |
| OTIS Mock AIME 2024-2025 | — | 95.6% |
| ProofBench | — | 26% |
| Omni-MATH | 48% | — |

## Knowledge

- Gemini 2.5 Flash-Lite: 32.1 (#206)
- Qwen3.7 Max: 61.7 (#24)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Expert | 1373 | 1488 |
| GPQA Diamond | — | 90.9% |
| SimpleQA Verified | — | 55.8% |
| MMLU-Pro | 53.7% | — |
| Vectara Hallucination Rate | 3.3% | — |
| GPQA (HELM) | 30.9% | — |

## Multimodal

- Gemini 2.5 Flash-Lite: 28.6 (#109)
- Qwen3.7 Max: —

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Vision | 1198 | — |
| VPCT | 30% | — |

## Multilingual

- Gemini 2.5 Flash-Lite: 49.5 (#129)
- Qwen3.7 Max: 57.1 (#13)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1369 | 1475 |
| LMArena Chinese | 1404 | 1533 |
| LMArena Russian | 1373 | 1482 |
| LMArena French | 1388 | — |
| LMArena German | 1390 | — |
| LMArena Japanese | 1359 | — |
| LMArena Korean | 1358 | — |
| LMArena Spanish | 1396 | — |

## Instruction Following

- Gemini 2.5 Flash-Lite: 70.2 (#163)
- Qwen3.7 Max: 76.9 (#34)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1366 | 1460 |
| IFEval | 81% | — |

## Long Context

- Gemini 2.5 Flash-Lite: 33.3 (#257)
- Qwen3.7 Max: 45.4 (#34)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1373 | 1484 |
| Fiction.LiveBench | 47.2% | — |

## Writing & Preference

- Gemini 2.5 Flash-Lite: 57.0 (#130)
- Qwen3.7 Max: 65.2 (#52)

| Benchmark | Gemini 2.5 Flash-Lite | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1379 | 1476 |
| LMArena Creative Writing | 1366 | 1450 |
| LMArena Multi-Turn | 1367 | 1482 |
| WildBench | 81.8% | — |
| EQ-Bench 4 | — | 1110 |

## FAQ

### Is Gemini 2.5 Flash-Lite better than Qwen3.7 Max?

Qwen3.7 Max is the stronger model overall, scoring 51.4 to 36.4 on the Noometry Index. Gemini 2.5 Flash-Lite costs 21× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.

### Which is cheaper, Gemini 2.5 Flash-Lite or Qwen3.7 Max?

Gemini 2.5 Flash-Lite is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.

### Is Gemini 2.5 Flash-Lite or Qwen3.7 Max better for coding?

Qwen3.7 Max scores higher on coding benchmarks: 50.2 versus 38.0 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Flash-Lite does, with 1.05M tokens against 1M.

### How many benchmarks do Gemini 2.5 Flash-Lite and Qwen3.7 Max share?

16 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and Qwen3.7 Max has 33.