Model comparison
Gemini 3.1 Flash-Lite vs Qwen3.6-27B
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemini 3.1 Flash-Lite #111 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 3.1 Flash-Lite and Qwen3.6-27B share 18 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to Gemini 3.1 Flash-Lite; 36 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 18
- Gemini 3.1 Flash-Lite only
- 2
- Qwen3.6-27B only
- 36
- Comparable categories
- 1 / 8
Pick Qwen3.6-27B if you want the stronger benchmark profile. Gemini 3.1 Flash-Lite only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6-27B has the cleaner BenchAlign overall profile here, landing at 53.82 versus 50.83. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.6-27B's sharpest advantage is in multimodal & grounded, where it averages 76.7 against 73.2. The single biggest benchmark swing on the page is CharXiv, 73.2% to 78.4%.
Gemini 3.1 Flash-Lite is also the more expensive model on tokens at $0.25 input / $1.50 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B is the reasoning model in the pair, while Gemini 3.1 Flash-Lite is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemini 3.1 Flash-Lite gives you the larger context window at 1M, compared with 262K for Qwen3.6-27B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Gemini 3.1 Flash-Lite | Δ | Qwen3.6-27B |
|---|---|---|---|
| Multimodal | Gemini 3.1 Flash-Lite73.2 | Margin→ 3.5 | Qwen3.6-27B76.7 |
| Agentic | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Knowledge | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Qwen3.6-27B53.3 |
| Math | Gemini 3.1 Flash-LiteNot measured | MarginNo overlap | Qwen3.6-27B89.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
CharXiv
MultimodalA 73.2%B 78.4%Winner: Qwen3.6-27BΔ 5.2CharXiv: Gemini 3.1 Flash-Lite scored 73.2%; Qwen3.6-27B scored 78.4%. Qwen3.6-27B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 3.1 Flash-Lite | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 3.1 Flash-Lite$0.25 input / $1.5 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | Gemini 3.1 Flash-Lite205 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 3.1 Flash-Lite7.50 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 3.1 Flash-Lite1M | Qwen3.6-27B262K | Gemini 3.1 Flash-Lite lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Qwen3.6-27B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 6.2% | 27.0% | Qwen3.6-27B leads |
| APEX-Agents-AASource | 12.2% | — | Not comparable |
| τ²-bench resultsSource | 31.3% | 94.2% | Qwen3.6-27B leads |
| GDPval-AASource | 7.1% | 32.0% | Qwen3.6-27B leads |
| GDPval-AASource | 642 | 1140 | Qwen3.6-27B leads |
| Gert LabsSource | 38.46% | 54.84% | Qwen3.6-27B leads |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
Coding9 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Qwen3.6-27B | Result |
|---|---|---|---|
| Vibe Code BenchSource | 0.00% | — | Not comparable |
| AA Coding IndexSource | 34.7% | 53.7% | Qwen3.6-27B leads |
| AA-SciCodeSource | 41.9% | 39.8% | Gemini 3.1 Flash-Lite leads |
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Qwen3.6-27B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 25.0% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 82.2% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 16.2% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -15.5% | -19.8% | Gemini 3.1 Flash-Lite leads |
| AA-Omniscience AccuracySource | 36.4% | 19.2% | Gemini 3.1 Flash-Lite leads |
| AA-Omniscience Hallucination RateSource | 81.6% | 48.3% | Qwen3.6-27B leads |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
Math5 benchmarks
MultimodalQwen3.6-27B wins16 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Qwen3.6-27B | Result |
|---|---|---|---|
| CharXivSource | 73.2% | 78.4% | Qwen3.6-27B leads |
| AA-MMMU-ProSource | 75.5% | 74.6% | Gemini 3.1 Flash-Lite leads |
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Gemini 3.1 Flash-Lite | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.2% | 67.6% | Gemini 3.1 Flash-Lite leads |
Frequently Asked Questions (2)
Which is better, Gemini 3.1 Flash-Lite or Qwen3.6-27B?
Qwen3.6-27B is ahead on BenchLM's BenchAlign leaderboard, 53.82 to 50.83. The biggest single separator in this matchup is CharXiv, where the scores are 73.2% and 78.4%.
Which is better for multimodal and grounded tasks, Gemini 3.1 Flash-Lite or Qwen3.6-27B?
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 76.7 versus 73.2. Inside this category, CharXiv is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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