Model comparison
Gemma 3 27B vs GPT-5.6 Sol
Head-to-head evidence from 16 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Gemma 3 27B #164 (Supported); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemma 3 27B and GPT-5.6 Sol share 16 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Gemma 3 27B; 30 to GPT-5.6 Sol.
Updated July 23, 2026- Shared results
- 16
- Gemma 3 27B only
- 0
- GPT-5.6 Sol only
- 30
- Comparable categories
- 0 / 8
Benchmark data for Gemma 3 27B and GPT-5.6 Sol is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 6 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.
GPT-5.6 Sol is priced at $5.00 input / $30.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 3 27B. GPT-5.6 Sol has the larger context window at 1M, compared with 32K for Gemma 3 27B.
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 3 27B | Δ | GPT-5.6 Sol |
|---|---|---|---|
| Agentic | Gemma 3 27BNot measured | MarginNo overlap | GPT-5.6 Sol92.0 |
| Coding | Gemma 3 27BNot measured | MarginNo overlap | GPT-5.6 Sol64.6 |
| Knowledge | Gemma 3 27BNot measured | MarginNo overlap | GPT-5.6 Sol94.6 |
| Math | Gemma 3 27BNot measured | MarginNo overlap | GPT-5.6 Sol87.5 |
| Multimodal | Gemma 3 27BNot measured | MarginNo overlap | GPT-5.6 Sol83.0 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemma 3 27B | GPT-5.6 Sol | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemma 3 27B$0 input / $0 output | GPT-5.6 Sol$5 input / $30 output | Gemma 3 27B has the lower combined listed price. |
| Generation speedtokens per second | Gemma 3 27B31 tok/s | GPT-5.6 SolNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemma 3 27B2.04 s | GPT-5.6 SolNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemma 3 27B32K | GPT-5.6 Sol1M | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Gemma 3 27B | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA Agentic IndexSource | 0.3% | 54.0% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 10.5% | 85.1% | GPT-5.6 Sol leads |
| GDPval-AASource | 0.0% | 61.8% | GPT-5.6 Sol leads |
| GDPval-AASource | -144 | 1736 | GPT-5.6 Sol leads |
| Terminal-Bench 2.0Source | — | 91.9% | Not comparable |
| BrowseCompSource | — | 92.2% | Not comparable |
| OSWorld 2.0Source | — | 62.6% | Not comparable |
| CyberGymSource | — | 84.5% | Not comparable |
| ExploitGymSource | — | 33.7% | Not comparable |
| ToolathlonSource | — | 58% | Not comparable |
| AA BriefcaseSource | — | 1501 | Not comparable |
| AA ITBenchSource | — | 56.2% | Not comparable |
| AA Tau3 BankingSource | — | 33.0% | Not comparable |
| AA AutomationBenchSource | — | 51.2% | Not comparable |
| AA Harvey LABSource | — | 87.2% | Not comparable |
| terminalBenchHardSource | — | 65.9% | Not comparable |
| aaTerminalBench21Source | — | 88% | Not comparable |
Coding8 benchmarks
| Benchmark | Gemma 3 27B | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA Coding IndexSource | 10.1% | 77.4% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 21.2% | 56.1% | GPT-5.6 Sol leads |
| SWE-bench ProSource | — | 64.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 91.9% | Not comparable |
| deepSweSource | — | 72.7% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 60.6% | Not comparable |
| cursorBench32Source | — | 67.2% | Not comparable |
| VulcanBench v3Source | — | 87.0% | Not comparable |
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | Gemma 3 27B | GPT-5.6 Sol | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 7.4% | 58.9% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 42.8% | 94.1% | GPT-5.6 Sol leads |
| AA-HLESource | 4.7% | 47.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | -65.9% | 21.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 12.5% | 58.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 89.5% | 88.8% | GPT-5.6 Sol leads |
| GPQASource | — | 94.6% | Not comparable |
| GPQA-DSource | — | 94.6% | Not comparable |
| HealthBench ProfessionalSource | — | 60.5% | Not comparable |
| HealthBench HardSource | — | 33.1% | Not comparable |
Math3 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Gemma 3 27B | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA-IFBenchSource | 31.8% | 72.7% | GPT-5.6 Sol leads |
Frequently Asked Questions (3)
Can I compare Gemma 3 27B and GPT-5.6 Sol 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 3 27B and GPT-5.6 Sol today?
Gemma 3 27B: $0.00 input / $0.00 output per 1M tokens GPT-5.6 Sol: $5.00 input / $30.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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