Model comparison
Gemma 4 26B A4B vs Qwen3.5-122B-A10B
Head-to-head evidence from 17 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); Qwen3.5-122B-A10B #47 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 26B A4B and Qwen3.5-122B-A10B share 17 comparable benchmark results. 2 of 8 categories are comparable. 3 results are unique to Gemma 4 26B A4B; 14 to Qwen3.5-122B-A10B.
Updated July 23, 2026- Shared results
- 17
- Gemma 4 26B A4B only
- 3
- Qwen3.5-122B-A10B only
- 14
- Comparable categories
- 2 / 8
Pick Qwen3.5-122B-A10B if you want the stronger benchmark profile. Gemma 4 26B A4B only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Confidence note. This is a partial-evidence comparison with 17 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
Qwen3.5-122B-A10B has the cleaner BenchAlign overall profile here, landing at 60.56 versus 57.96. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.5-122B-A10B's sharpest advantage is in knowledge, where it averages 83.6 against 43.4. The single biggest benchmark swing on the page is MMLU-Pro, 82.6% to 86.7%.
Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B |
|---|---|---|---|
| Knowledge | Gemma 4 26B A4B43.4 | Margin→ 40.2 | Qwen3.5-122B-A10B83.6 |
| Multimodal | Gemma 4 26B A4B73.8 | Margin→ 3.4 | Qwen3.5-122B-A10B77.2 |
| Agentic | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.5-122B-A10B56.4 |
| Coding | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.5-122B-A10B72.0 |
| Reasoning | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.5-122B-A10B60.2 |
| Multilingual | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.5-122B-A10B82.2 |
| Inst. Following | Gemma 4 26B A4BNot measured | MarginNo overlap | Qwen3.5-122B-A10B93.4 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 82.6%B 86.7%Winner: Qwen3.5-122B-A10BΔ 4.1MMLU-Pro: Gemma 4 26B A4B scored 82.6%; Qwen3.5-122B-A10B scored 86.7%. Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 26B A4B$0 input / $0 output | Qwen3.5-122B-A10B$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Gemma 4 26B A4BNot available | Qwen3.5-122B-A10BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 26B A4BNot available | Qwen3.5-122B-A10BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 26B A4B256K | Qwen3.5-122B-A10B262K | Qwen3.5-122B-A10B lists the larger context window. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | Gemma 4 26B A4B | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| AA Agentic IndexSource | 11.0% | 20.7% | Qwen3.5-122B-A10B leads |
| τ²-bench resultsSource | 43.6% | 93.6% | Qwen3.5-122B-A10B leads |
| GDPval-AASource | 13.1% | 23.9% | Qwen3.5-122B-A10B leads |
| GDPval-AASource | 761 | 978 | Qwen3.5-122B-A10B leads |
| Terminal-Bench 2.0Source | — | 49.4% | Not comparable |
| BrowseCompSource | — | 63.8% | Not comparable |
| OSWorld-VerifiedSource | — | 58% | Not comparable |
Coding3 benchmarks
Reasoning3 benchmarks
KnowledgeQwen3.5-122B-A10B wins11 benchmarks
| Benchmark | Gemma 4 26B A4B | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| MMLU-ProSource | 82.6% | 86.7% | Qwen3.5-122B-A10B leads |
| HLESource | 17.2% | — | Not comparable |
| HLE w/o toolsSource | 8.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 25.7% | 32.3% | Qwen3.5-122B-A10B leads |
| AA-GPQA DiamondSource | 79.2% | 85.7% | Qwen3.5-122B-A10B leads |
| AA-HLESource | 18.3% | 23.4% | Qwen3.5-122B-A10B leads |
| AA-Omniscience IndexSource | -48.1% | -39.6% | Qwen3.5-122B-A10B leads |
| AA-Omniscience AccuracySource | 18.2% | 24.7% | Qwen3.5-122B-A10B leads |
| AA-Omniscience Hallucination RateSource | 80.9% | 85.5% | Gemma 4 26B A4B leads |
| SuperGPQASource | — | 67.1% | Not comparable |
| GPQASource | — | 86.6% | Not comparable |
Multilingual1 benchmarks
| Benchmark | Gemma 4 26B A4B | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 82.2% | Not comparable |
MultimodalQwen3.5-122B-A10B wins7 benchmarks
Frequently Asked Questions (3)
Which is better, Gemma 4 26B A4B or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B is ahead on BenchLM's BenchAlign leaderboard, 60.56 to 57.96. The biggest single separator in this matchup is MMLU-Pro, where the scores are 82.6% and 86.7%.
Which is better for knowledge tasks, Gemma 4 26B A4B or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 83.6 versus 43.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, Gemma 4 26B A4B or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B has the edge for multimodal and grounded tasks in this comparison, averaging 77.2 versus 73.8. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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