Model comparison
GPT-5.5 vs Llama 4 Maverick
Head-to-head evidence from 18 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.5 #9 (Estimated); Llama 4 Maverick #191 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.5 and Llama 4 Maverick share 18 comparable benchmark results. 1 of 8 categories are comparable. 39 results are unique to GPT-5.5; 0 to Llama 4 Maverick.
Updated July 22, 2026- Shared results
- 18
- GPT-5.5 only
- 39
- Llama 4 Maverick only
- 0
- Comparable categories
- 1 / 8
Pick GPT-5.5 if you want the stronger benchmark profile. Llama 4 Maverick only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 7 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-5.5 is clearly ahead on the BenchAlign aggregate, 73.51 to 23.49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.5's sharpest advantage is in mathematics, where it averages 47.6 against 0.7. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 51.700% to 0.690%.
GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Maverick. That is roughly Infinityx on output cost alone. GPT-5.5 is the reasoning model in the pair, while Llama 4 Maverick 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.
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-5.5 | Δ | Llama 4 Maverick |
|---|---|---|---|
| Math | GPT-5.547.6 | Margin← 46.9 | Llama 4 Maverick0.7 |
| Agentic | GPT-5.581.6 | MarginNo overlap | Llama 4 MaverickNot measured |
| Coding | GPT-5.558.6 | MarginNo overlap | Llama 4 MaverickNot measured |
| Reasoning | GPT-5.585.0 | MarginNo overlap | Llama 4 MaverickNot measured |
| Knowledge | GPT-5.557.8 | MarginNo overlap | Llama 4 MaverickNot measured |
| Multimodal | GPT-5.570.4 | MarginNo overlap | Llama 4 MaverickNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 51.700%B 0.690%Winner: GPT-5.5Δ 51FrontierMath v2 (Tiers 1-3): GPT-5.5 scored 51.700%; Llama 4 Maverick scored 0.690%. GPT-5.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.5 | Llama 4 Maverick | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.5$5 input / $30 output | Llama 4 Maverick$0 input / $0 output | Llama 4 Maverick has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.5Not available | Llama 4 Maverick121 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.5Not available | Llama 4 Maverick0.95 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.51M | Llama 4 Maverick1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic24 benchmarks
| Benchmark | GPT-5.5 | Llama 4 Maverick | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 82% | — | Not comparable |
| CyberGymSource | 81.8% | — | Not comparable |
| BrowseCompSource | 84.4% | — | Not comparable |
| OSWorld-VerifiedSource | 78.7% | — | Not comparable |
| MCP AtlasSource | 75.3% | — | Not comparable |
| ToolathlonSource | 55.6% | — | Not comparable |
| τ²-bench resultsSource | 93.9% | 17.8% | GPT-5.5 leads |
| AA Agentic IndexSource | 44.9% | 1.3% | GPT-5.5 leads |
| APEX-Agents-AASource | 37.7% | — | Not comparable |
| GDPval-AASource | 49.5% | 0.0% | GPT-5.5 leads |
| GDPval-AASource | 1490 | -16 | GPT-5.5 leads |
| Gert LabsSource | 72.93% | — | Not comparable |
| ResearchClawBenchSource | 17.0% | — | Not comparable |
| OSWorld 2.0Source | 13.0% | — | Not comparable |
| JobBenchSource | 42.7% | — | Not comparable |
| ExploitGymSource | 13.4% | — | Not comparable |
| AA BriefcaseSource | 1154 | — | Not comparable |
| AA AutomationBenchSource | 42.1% | — | Not comparable |
| AA EnterpriseOps-GymSource | 46.6% | — | Not comparable |
| AA Harvey LABSource | 86.3% | — | Not comparable |
| AA ITBenchSource | 45.8% | — | Not comparable |
| AA Tau3 BankingSource | 31.3% | — | Not comparable |
| terminalBenchHardSource | 60.6% | — | Not comparable |
| aaTerminalBench21Source | 84.3% | — | Not comparable |
Coding9 benchmarks
| Benchmark | GPT-5.5 | Llama 4 Maverick | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.6% | — | Not comparable |
| Terminal-Bench 2.0Source | 82.0% | — | Not comparable |
| Vibe Code BenchSource | 69.85% | — | Not comparable |
| React Native EvalsSource | 84.7% | — | Not comparable |
| cursorBench31Source | 59.2% | — | Not comparable |
| cursorBench32Source | 58.4% | — | Not comparable |
| AA Coding IndexSource | 74.9% | 16.3% | GPT-5.5 leads |
| AA-SciCodeSource | 56.1% | 33.1% | GPT-5.5 leads |
| FrontierCode 1.1 MainSource | 43.0% | — | Not comparable |
Reasoning5 benchmarks
Knowledge10 benchmarks
| Benchmark | GPT-5.5 | Llama 4 Maverick | Result |
|---|---|---|---|
| GPQASource | 93.6% | — | Not comparable |
| GPQA-DSource | 93.6% | — | Not comparable |
| HLESource | 52.2% | — | Not comparable |
| HLE w/o toolsSource | 41.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 54.8% | 14.3% | GPT-5.5 leads |
| AA-GPQA DiamondSource | 93.5% | 67.1% | GPT-5.5 leads |
| AA-HLESource | 44.3% | 4.8% | GPT-5.5 leads |
| AA-Omniscience IndexSource | 20.1% | -41.8% | GPT-5.5 leads |
| AA-Omniscience AccuracySource | 56.9% | 24.3% | GPT-5.5 leads |
| AA-Omniscience Hallucination RateSource | 85.5% | 87.3% | GPT-5.5 leads |
MathGPT-5.5 wins3 benchmarks
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.5 | Llama 4 Maverick | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.9% | 43.0% | GPT-5.5 leads |
Frequently Asked Questions (2)
Which is better, GPT-5.5 or Llama 4 Maverick?
GPT-5.5 is ahead on BenchLM's BenchAlign leaderboard, 73.51 to 23.49. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 51.700% and 0.690%.
Which is better for math, GPT-5.5 or Llama 4 Maverick?
GPT-5.5 has the edge for math in this comparison, averaging 47.6 versus 0.7. Inside this category, FrontierMath v2 (Tiers 1-3) 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.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.