Model comparison
Command A+ vs GPT-5.6 Sol
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Command A+ #135 (Estimated); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Command A+ and GPT-5.6 Sol share 18 comparable benchmark results. 1 of 8 categories are comparable. 3 results are unique to Command A+; 28 to GPT-5.6 Sol.
Updated July 23, 2026- Shared results
- 18
- Command A+ only
- 3
- GPT-5.6 Sol only
- 28
- Comparable categories
- 1 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Command A+ only becomes the better choice if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.6 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 47.51. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol's sharpest advantage is in multimodal & grounded, where it averages 83 against 59.3. The single biggest benchmark swing on the page is MMMU-Pro, 63% to 83%.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $2.50 input / $10.00 output per 1M tokens for Command A+. That is roughly 3.0x on output cost alone. GPT-5.6 Sol gives you the larger context window at 1M, compared with 128K for Command A+.
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 | Command A+ | Δ | GPT-5.6 Sol |
|---|---|---|---|
| Multimodal | Command A+59.3 | Margin→ 23.7 | GPT-5.6 Sol83.0 |
| Agentic | Command A+Not measured | MarginNo overlap | GPT-5.6 Sol92.0 |
| Coding | Command A+Not measured | MarginNo overlap | GPT-5.6 Sol64.6 |
| Knowledge | Command A+Not measured | MarginNo overlap | GPT-5.6 Sol94.6 |
| Math | Command A+Not measured | MarginNo overlap | GPT-5.6 Sol87.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMMU-Pro
MultimodalA 63%B 83%Winner: GPT-5.6 SolΔ 20MMMU-Pro: Command A+ scored 63%; GPT-5.6 Sol scored 83%. GPT-5.6 Sol wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Command A+ | GPT-5.6 Sol | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Command A+$2.5 input / $10 output | GPT-5.6 Sol$5 input / $30 output | Command A+ has the lower combined listed price. |
| Generation speedtokens per second | Command A+272 tok/s | GPT-5.6 SolNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Command A+0.25 s | GPT-5.6 SolNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Command A+128K | GPT-5.6 Sol1M | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Command A+ | GPT-5.6 Sol | Result |
|---|---|---|---|
| τ²-bench resultsSource | 80.7% | 85.1% | GPT-5.6 Sol leads |
| AA Agentic IndexSource | 9.2% | 54.0% | GPT-5.6 Sol leads |
| GDPval-AASource | 10.7% | 61.8% | GPT-5.6 Sol leads |
| GDPval-AASource | 714 | 1736 | GPT-5.6 Sol leads |
| terminalBenchHardSource | 25% | 65.9% | 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 |
| aaTerminalBench21Source | — | 88% | Not comparable |
Coding8 benchmarks
| Benchmark | Command A+ | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA Coding IndexSource | 27.9% | 77.4% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 37.8% | 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
Knowledge11 benchmarks
| Benchmark | Command A+ | GPT-5.6 Sol | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 22.5% | 58.9% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 76.1% | 94.1% | GPT-5.6 Sol leads |
| AA-HLESource | 11.4% | 47.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | -4.0% | 21.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 8.9% | 58.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 14.1% | 88.8% | Command A+ leads |
| AA Openness IndexSource | 38.9% | — | Not comparable |
| 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
MultimodalGPT-5.6 Sol wins5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Command A+ | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.9% | 72.7% | Command A+ leads |
Frequently Asked Questions (2)
Which is better, Command A+ or GPT-5.6 Sol?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 47.51. The biggest single separator in this matchup is MMMU-Pro, where the scores are 63% and 83%.
Which is better for multimodal and grounded tasks, Command A+ or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 59.3. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
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