Model comparison
Gemma 4 31B vs Ling 2.6 Flash
Head-to-head evidence from 16 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 31B #43 (Supported); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 31B and Ling 2.6 Flash share 16 comparable benchmark results. 2 of 8 categories are comparable. 13 results are unique to Gemma 4 31B; 2 to Ling 2.6 Flash.
Updated July 21, 2026- Shared results
- 16
- Gemma 4 31B only
- 13
- Ling 2.6 Flash only
- 2
- Comparable categories
- 2 / 8
Pick Gemma 4 31B if you want the stronger benchmark profile. Ling 2.6 Flash 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 16 shared benchmark results across 5 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 31B is clearly ahead on the BenchAlign aggregate, 61.08 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemma 4 31B's sharpest advantage is in coding, where it averages 41.6 against 27. The single biggest benchmark swing on the page is GPQA, 84.3% to 59%. Ling 2.6 Flash does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Gemma 4 31B is the reasoning model in the pair, while Ling 2.6 Flash 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. Ling 2.6 Flash gives you the larger context window at 262K, compared with 256K for Gemma 4 31B.
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 31B | Δ | Ling 2.6 Flash |
|---|---|---|---|
| Coding | Gemma 4 31B41.6 | Margin← 14.6 | Ling 2.6 Flash27.0 |
| Knowledge | Gemma 4 31B52.9 | Margin→ 6.1 | Ling 2.6 Flash59.0 |
| Multimodal | Gemma 4 31B76.9 | MarginNo overlap | Ling 2.6 FlashNot measured |
| Inst. Following | Gemma 4 31BNot measured | MarginNo overlap | Ling 2.6 Flash57.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 84.3%B 59%Winner: Gemma 4 31BΔ 25.3GPQA: Gemma 4 31B scored 84.3%; Ling 2.6 Flash scored 59%. Gemma 4 31B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 31B | Ling 2.6 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 31B$0 input / $0 output | Ling 2.6 FlashNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 31BNot available | Ling 2.6 Flash209.5 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 31BNot available | Ling 2.6 Flash1.07 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 31B256K | Ling 2.6 Flash262K | Ling 2.6 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | Gemma 4 31B | Ling 2.6 Flash | Result |
|---|---|---|---|
| AA Agentic IndexSource | 14.4% | 2.3% | Gemma 4 31B leads |
| τ²-bench resultsSource | 59.9% | 86% | Ling 2.6 Flash leads |
| GDPval-AASource | 15.2% | 2.2% | Gemma 4 31B leads |
| GDPval-AASource | 804 | 545 | Gemma 4 31B leads |
| Gert LabsSource | 35.26% | — | Not comparable |
| AA EnterpriseOps-GymSource | 28.3% | — | Not comparable |
| AA ITBenchSource | 37.3% | — | Not comparable |
| AA Tau3 BankingSource | 15.1% | — | Not comparable |
| terminalBenchHardSource | 36.4% | — | Not comparable |
CodingGemma 4 31B wins5 benchmarks
Reasoning2 benchmarks
KnowledgeLing 2.6 Flash wins11 benchmarks
| Benchmark | Gemma 4 31B | Ling 2.6 Flash | Result |
|---|---|---|---|
| GPQASource | 84.3% | 59% | Gemma 4 31B leads |
| MMLU-ProSource | 85.2% | — | Not comparable |
| HLESource | 26.5% | — | Not comparable |
| HLE w/o toolsSource | 19.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 29.4% | 14.1% | Gemma 4 31B leads |
| AA-GPQA DiamondSource | 85.7% | 59.3% | Gemma 4 31B leads |
| AA-HLESource | 22.7% | 6.2% | Gemma 4 31B leads |
| AA-Omniscience IndexSource | -45.4% | -65.7% | Gemma 4 31B leads |
| AA-Omniscience AccuracySource | 19.9% | 15.4% | Gemma 4 31B leads |
| AA-Omniscience Hallucination RateSource | 81.6% | 95.8% | Gemma 4 31B leads |
| AA Openness IndexSource | 38.9% | — | Not comparable |
Multimodal2 benchmarks
Frequently Asked Questions (3)
Which is better, Gemma 4 31B or Ling 2.6 Flash?
Gemma 4 31B is ahead on BenchLM's BenchAlign leaderboard, 61.08 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 84.3% and 59%.
Which is better for knowledge tasks, Gemma 4 31B or Ling 2.6 Flash?
Ling 2.6 Flash has the edge for knowledge tasks in this comparison, averaging 59 versus 52.9. Inside this category, AA-GPQA Diamond is the benchmark that creates the most daylight between them.
Which is better for coding, Gemma 4 31B or Ling 2.6 Flash?
Gemma 4 31B has the edge for coding in this comparison, averaging 41.6 versus 27. Inside this category, AA Coding Index 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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