Model comparison
Gemma 4 12B vs Qwen3 235B 2507
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 12B #137 (Estimated); Qwen3 235B 2507 #78 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 12B and Qwen3 235B 2507 share 2 comparable benchmark results. 1 of 8 categories are comparable. 21 results are unique to Gemma 4 12B; 2 to Qwen3 235B 2507.
Updated July 23, 2026- Shared results
- 2
- Gemma 4 12B only
- 21
- Qwen3 235B 2507 only
- 2
- Comparable categories
- 1 / 8
Pick Qwen3 235B 2507 if you want the stronger benchmark profile. Gemma 4 12B only becomes the better choice if you need the larger 256K context window or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 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 235B 2507 is clearly ahead on the BenchAlign aggregate, 56.02 to 47.29. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3 235B 2507's sharpest advantage is in knowledge, where it averages 78.9 against 77.5. The single biggest benchmark swing on the page is MMLU-Pro, 77.2% to 83%.
Gemma 4 12B is the reasoning model in the pair, while Qwen3 235B 2507 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. Gemma 4 12B gives you the larger context window at 256K, compared with 128K for Qwen3 235B 2507.
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 12B | Δ | Qwen3 235B 2507 |
|---|---|---|---|
| Knowledge | Gemma 4 12B77.5 | Margin→ 1.4 | Qwen3 235B 250778.9 |
| Reasoning | Gemma 4 12B43.4 | MarginNo overlap | Qwen3 235B 2507Not measured |
| Math | Gemma 4 12B77.5 | MarginNo overlap | Qwen3 235B 2507Not measured |
| Multilingual | Gemma 4 12BNot measured | MarginNo overlap | Qwen3 235B 250779.4 |
| Multimodal | Gemma 4 12B69.1 | MarginNo overlap | Qwen3 235B 2507Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 77.2%B 83%Winner: Qwen3 235B 2507Δ 5.8MMLU-Pro: Gemma 4 12B scored 77.2%; Qwen3 235B 2507 scored 83%. Qwen3 235B 2507 wins this benchmark. - Source ↗
GPQA
KnowledgeA 78.8%B 77.5%Winner: Gemma 4 12BΔ 1.3GPQA: Gemma 4 12B scored 78.8%; Qwen3 235B 2507 scored 77.5%. Gemma 4 12B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 12B | Qwen3 235B 2507 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 12BNot available | Qwen3 235B 2507$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 12BNot available | Qwen3 235B 2507Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 12BNot available | Qwen3 235B 2507Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 12B256K | Qwen3 235B 2507128K | Gemma 4 12B lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Gemma 4 12B | Qwen3 235B 2507 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 36.3% | — | Not comparable |
Coding1 benchmarks
| Benchmark | Gemma 4 12B | Qwen3 235B 2507 | Result |
|---|---|---|---|
| AA-SciCodeSource | 38.2% | — | Not comparable |
Reasoning4 benchmarks
KnowledgeQwen3 235B 2507 wins12 benchmarks
| Benchmark | Gemma 4 12B | Qwen3 235B 2507 | Result |
|---|---|---|---|
| GPQASource | 78.8% | 77.5% | Gemma 4 12B leads |
| GPQA-DSource | 78.8% | — | Not comparable |
| MMLU-ProSource | 77.2% | 83% | Qwen3 235B 2507 leads |
| HLE w/o toolsSource | 5.2% | — | Not comparable |
| MMMLUSource | 83.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 22.0% | — | Not comparable |
| AA-GPQA DiamondSource | 75.3% | — | Not comparable |
| AA-HLESource | 14.8% | — | Not comparable |
| AA-Omniscience IndexSource | -51.9% | — | Not comparable |
| AA-Omniscience AccuracySource | 16.0% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 80.8% | — | Not comparable |
| SuperGPQASource | — | 62.6% | Not comparable |
Math1 benchmarks
| Benchmark | Gemma 4 12B | Qwen3 235B 2507 | Result |
|---|---|---|---|
| AIME26Source | 77.5% | — | Not comparable |
Multilingual1 benchmarks
| Benchmark | Gemma 4 12B | Qwen3 235B 2507 | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 79.4% | Not comparable |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemma 4 12B | Qwen3 235B 2507 | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.5% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, Gemma 4 12B or Qwen3 235B 2507?
Qwen3 235B 2507 is ahead on BenchLM's BenchAlign leaderboard, 56.02 to 47.29. The biggest single separator in this matchup is MMLU-Pro, where the scores are 77.2% and 83%.
Which is better for knowledge tasks, Gemma 4 12B or Qwen3 235B 2507?
Qwen3 235B 2507 has the edge for knowledge tasks in this comparison, averaging 78.9 versus 77.5. Inside this category, MMLU-Pro is the benchmark that creates the most daylight between them.
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