Model comparison
Gemma 4 31B vs SWE-1.7
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 4 31B #43 (Supported); SWE-1.7 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 4 31B and SWE-1.7 share 0 comparable benchmark results. 0 of 8 categories are comparable. 30 results are unique to Gemma 4 31B; 4 to SWE-1.7.
Updated July 18, 2026- Shared results
- 0
- Gemma 4 31B only
- 30
- SWE-1.7 only
- 4
- Comparable categories
- 0 / 8
Benchmark data for Gemma 4 31B and SWE-1.7 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 4 31B | SWE-1.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 4 31B$0 input / $0 output | SWE-1.7Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemma 4 31BNot available | SWE-1.7Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 4 31BNot available | SWE-1.7Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 4 31B256K | SWE-1.7256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | Gemma 4 31B | SWE-1.7 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 14.4% | — | Not comparable |
| τ²-bench resultsSource | 59.9% | — | Not comparable |
| GDPval-AASource | 15.2% | — | Not comparable |
| GDPval-AASource | 804 | — | Not comparable |
| Gert LabsSource | 35.26% | — | Not comparable |
| AA EnterpriseOps-GymSource | 28.3% | — | Not comparable |
| AA Harvey LABSource | 0.0% | — | Not comparable |
| AA ITBenchSource | 37.3% | — | Not comparable |
| AA Tau3 BankingSource | 15.1% | — | Not comparable |
| terminalBenchHardSource | 36.4% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 81.5% | Not comparable |
Coding7 benchmarks
| Benchmark | Gemma 4 31B | SWE-1.7 | Result |
|---|---|---|---|
| SWE-RebenchSource | 41.6% | — | Not comparable |
| React Native EvalsSource | 75.2% | — | Not comparable |
| AA Coding IndexSource | 43.4% | — | Not comparable |
| AA-SciCodeSource | 43.4% | — | Not comparable |
| FrontierCode 1.1 MainSource | — | 42.3% | Not comparable |
| Terminal-Bench 2.0Source | — | 81.5% | Not comparable |
| SWE MultilingualSource | — | 77.8% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Gemma 4 31B | SWE-1.7 | Result |
|---|---|---|---|
| GPQASource | 84.3% | — | Not comparable |
| 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% | — | Not comparable |
| AA-GPQA DiamondSource | 85.7% | — | Not comparable |
| AA-HLESource | 22.7% | — | Not comparable |
| AA-Omniscience IndexSource | -45.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 19.9% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 81.6% | — | Not comparable |
| AA Openness IndexSource | 38.9% | — | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemma 4 31B | SWE-1.7 | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.6% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Gemma 4 31B and SWE-1.7 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Gemma 4 31B and SWE-1.7 today?
Gemma 4 31B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Related Comparisons
Explore More
The AI models change fast. We track them for you.
A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.