Model comparison
Gemma 4 26B A4B vs Qwen3.6-27B
Head-to-head evidence from 19 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 26B A4B #67 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 26B A4B and Qwen3.6-27B share 19 comparable benchmark results. 2 of 8 categories are comparable. 1 result is unique to Gemma 4 26B A4B; 35 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 19
- Gemma 4 26B A4B only
- 1
- Qwen3.6-27B only
- 35
- Comparable categories
- 2 / 8
Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if knowledge is the priority or you need the larger 262K context window.
Confidence note. This is a partial-evidence comparison with 19 shared benchmark results across 6 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Gemma 4 26B A4B is clearly ahead on the BenchAlign aggregate, 57.96 to 53.82. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-27B gives you the larger context window at 262K, compared with 256K for Gemma 4 26B A4B.
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 | Gemma 4 26B A4B | Δ | Qwen3.6-27B |
|---|---|---|---|
| Knowledge | Gemma 4 26B A4B43.4 | Margin→ 9.9 | Qwen3.6-27B53.3 |
| Multimodal | Gemma 4 26B A4B73.8 | Margin→ 2.9 | Qwen3.6-27B76.7 |
| Agentic | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Math | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.6-27B89.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 17.2%B 24%Winner: Qwen3.6-27BΔ 6.8HLE: Gemma 4 26B A4B scored 17.2%; Qwen3.6-27B scored 24%. Qwen3.6-27B wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 82.6%B 86.2%Winner: Qwen3.6-27BΔ 3.6MMLU-Pro: Gemma 4 26B A4B scored 82.6%; Qwen3.6-27B scored 86.2%. Qwen3.6-27B wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 73.8%B 75.8%Winner: Qwen3.6-27BΔ 2MMMU-Pro: Gemma 4 26B A4B scored 73.8%; Qwen3.6-27B scored 75.8%. Qwen3.6-27B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 26B A4B | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 26B A4B$0 input / $0 output | Qwen3.6-27B$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Gemma 4 26B A4BNot available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 26B A4BNot available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 26B A4B256K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Gemma 4 26B A4B | Qwen3.6-27B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 11.0% | 27.0% | Qwen3.6-27B leads |
| τ²-bench resultsSource | 43.6% | 94.2% | Qwen3.6-27B leads |
| GDPval-AASource | 13.1% | 32.0% | Qwen3.6-27B leads |
| GDPval-AASource | 761 | 1140 | 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 |
| Gert LabsSource | — | 54.84% | Not comparable |
Coding8 benchmarks
| Benchmark | Gemma 4 26B A4B | Qwen3.6-27B | Result |
|---|---|---|---|
| AA Coding IndexSource | 39.3% | 53.7% | Qwen3.6-27B leads |
| AA-SciCodeSource | 40.0% | 39.8% | Gemma 4 26B A4B 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
KnowledgeQwen3.6-27B wins13 benchmarks
| Benchmark | Gemma 4 26B A4B | Qwen3.6-27B | Result |
|---|---|---|---|
| MMLU-ProSource | 82.6% | 86.2% | Qwen3.6-27B leads |
| HLESource | 17.2% | 24% | Qwen3.6-27B leads |
| HLE w/o toolsSource | 8.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 25.7% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 79.2% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 18.3% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -48.1% | -19.8% | Qwen3.6-27B leads |
| AA-Omniscience AccuracySource | 18.2% | 19.2% | Qwen3.6-27B leads |
| AA-Omniscience Hallucination RateSource | 80.9% | 48.3% | Qwen3.6-27B leads |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
Math5 benchmarks
MultimodalQwen3.6-27B wins16 benchmarks
| Benchmark | Gemma 4 26B A4B | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMU-ProSource | 73.8% | 75.8% | Qwen3.6-27B leads |
| AA-MMMU-ProSource | 69.2% | 74.6% | Qwen3.6-27B leads |
| MMMUSource | — | 82.9% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | 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 | Gemma 4 26B A4B | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.4% | 67.6% | Gemma 4 26B A4B leads |
Frequently Asked Questions (3)
Which is better, Gemma 4 26B A4B or Qwen3.6-27B?
Gemma 4 26B A4B is ahead on BenchLM's BenchAlign leaderboard, 57.96 to 53.82. The biggest single separator in this matchup is HLE, where the scores are 17.2% and 24%.
Which is better for knowledge tasks, Gemma 4 26B A4B or Qwen3.6-27B?
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 53.3 versus 43.4. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Gemma 4 26B A4B or Qwen3.6-27B?
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 76.7 versus 73.8. Inside this category, AA-MMMU-Pro 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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