Model comparison
GPT-5.6 Sol vs Grok 4.20
Head-to-head evidence from 5 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.6 Sol #3 (Supported); Grok 4.20 #88 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.6 Sol and Grok 4.20 share 5 comparable benchmark results. 3 of 8 categories are comparable. 41 results are unique to GPT-5.6 Sol; 13 to Grok 4.20.
Updated July 23, 2026- Shared results
- 5
- GPT-5.6 Sol only
- 41
- Grok 4.20 only
- 13
- Comparable categories
- 3 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. Grok 4.20 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 4 evidence categories; 3 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 54.68. 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 agentic, where it averages 92 against 47.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 91.9% to 47.1%. Grok 4.20 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $2.00 input / $6.00 output per 1M tokens for Grok 4.20. That is roughly 5.0x on output cost alone. Grok 4.20 gives you the larger context window at 2M, compared with 1M for GPT-5.6 Sol.
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 | GPT-5.6 Sol | Δ | Grok 4.20 |
|---|---|---|---|
| Agentic | GPT-5.6 Sol92.0 | Margin← 44.9 | Grok 4.2047.1 |
| Multimodal | GPT-5.6 Sol83.0 | Margin← 12.9 | Grok 4.2070.1 |
| Coding | GPT-5.6 Sol64.6 | Margin→ 2.5 | Grok 4.2067.1 |
| Reasoning | GPT-5.6 SolNot measured | MarginNo overlap | Grok 4.2053.3 |
| Knowledge | GPT-5.6 Sol94.6 | MarginNo overlap | Grok 4.20Not measured |
| Math | GPT-5.6 Sol87.5 | MarginNo overlap | Grok 4.20Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 91.9%B 47.1%Winner: GPT-5.6 SolΔ 44.8Terminal-Bench 2.0: GPT-5.6 Sol scored 91.9%; Grok 4.20 scored 47.1%. GPT-5.6 Sol wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 64.6%B 51.8%Winner: GPT-5.6 SolΔ 12.8SWE-bench Pro: GPT-5.6 Sol scored 64.6%; Grok 4.20 scored 51.8%. GPT-5.6 Sol wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 83%B 75.2%Winner: GPT-5.6 SolΔ 7.8MMMU-Pro: GPT-5.6 Sol scored 83%; Grok 4.20 scored 75.2%. 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 | GPT-5.6 Sol | Grok 4.20 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.6 Sol$5 input / $30 output | Grok 4.20$2 input / $6 output | Grok 4.20 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.6 SolNot available | Grok 4.20233 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.6 SolNot available | Grok 4.2010.33 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.6 Sol1M | Grok 4.202M | Grok 4.20 lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins19 benchmarks
| Benchmark | GPT-5.6 Sol | Grok 4.20 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 91.9% | 47.1% | GPT-5.6 Sol leads |
| 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 Agentic IndexSource | 54.0% | — | Not comparable |
| τ²-bench resultsSource | 85.1% | — | Not comparable |
| GDPval-AASource | 61.8% | — | Not comparable |
| GDPval-AASource | 1736 | — | 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 |
| DeepSearchQASource | — | 62.8% | Not comparable |
| Gert LabsSource | — | 38.36% | Not comparable |
CodingGrok 4.20 wins11 benchmarks
| Benchmark | GPT-5.6 Sol | Grok 4.20 | Result |
|---|---|---|---|
| SWE-bench ProSource | 64.6% | 51.8% | GPT-5.6 Sol leads |
| 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 |
| AA Coding IndexSource | 77.4% | — | Not comparable |
| AA-SciCodeSource | 56.1% | — | Not comparable |
| LiveCodeBench ProSource | — | 74.2% | Not comparable |
| SWE-bench VerifiedSource | — | 76.7% | Not comparable |
| Vibe Code BenchSource | — | 4.06% | Not comparable |
Reasoning5 benchmarks
Knowledge12 benchmarks
| Benchmark | GPT-5.6 Sol | Grok 4.20 | Result |
|---|---|---|---|
| GPQASource | 94.6% | — | Not comparable |
| GPQA-DSource | 94.6% | 88.5% | GPT-5.6 Sol leads |
| HealthBench ProfessionalSource | 60.5% | — | Not comparable |
| HealthBench HardSource | 33.1% | 20.3% | GPT-5.6 Sol leads |
| Artificial Analysis Intelligence IndexSource | 58.9% | — | Not comparable |
| AA-GPQA DiamondSource | 94.1% | — | Not comparable |
| AA-HLESource | 47.2% | — | Not comparable |
| AA-Omniscience IndexSource | 21.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 58.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 88.8% | — | Not comparable |
| HLE w/o toolsSource | — | 31.6% | Not comparable |
| MedXpertQA (Text)Source | — | 50.2% | Not comparable |
Math3 benchmarks
MultimodalGPT-5.6 Sol wins8 benchmarks
| Benchmark | GPT-5.6 Sol | Grok 4.20 | Result |
|---|---|---|---|
| MMMU-ProSource | 83% | 75.2% | GPT-5.6 Sol leads |
| MMMU-Pro w/ PythonSource | 84.6% | — | Not comparable |
| AA-MMMU-ProSource | 83.4% | — | Not comparable |
| CharXivSource | — | 60.9% | Not comparable |
| ERQASource | — | 54.1% | Not comparable |
| SimpleVQASource | — | 57.4% | Not comparable |
| MedXpertQA (MM)Source | — | 65.8% | Not comparable |
| Design Arena WebsiteSource | — | 1257 | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.6 Sol | Grok 4.20 | Result |
|---|---|---|---|
| AA-IFBenchSource | 72.7% | — | Not comparable |
Frequently Asked Questions (4)
Which is better, GPT-5.6 Sol or Grok 4.20?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 54.68. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 91.9% and 47.1%.
Which is better for coding, GPT-5.6 Sol or Grok 4.20?
Grok 4.20 has the edge for coding in this comparison, averaging 67.1 versus 64.6. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.6 Sol or Grok 4.20?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 47.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.6 Sol or Grok 4.20?
GPT-5.6 Sol has the edge for multimodal and grounded tasks in this comparison, averaging 83 versus 70.1. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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