Model comparison
Llama 4 Maverick vs o3-pro
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Llama 4 Maverick #191 (Supported); o3-pro #127 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Maverick and o3-pro share 2 comparable benchmark results. 0 of 8 categories are comparable. 16 results are unique to Llama 4 Maverick; 0 to o3-pro.
Updated July 22, 2026- Shared results
- 2
- Llama 4 Maverick only
- 16
- o3-pro only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Llama 4 Maverick and o3-pro is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 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.
o3-pro is priced at $20.00 input / $80.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Maverick. Llama 4 Maverick has the larger context window at 1M, compared with 200K for o3-pro.
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 | Llama 4 Maverick | Δ | o3-pro |
|---|---|---|---|
| Math | Llama 4 Maverick0.7 | MarginNo overlap | o3-proNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Llama 4 Maverick | o3-pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Maverick$0 input / $0 output | o3-pro$20 input / $80 output | Llama 4 Maverick has the lower combined listed price. |
| Generation speedtokens per second | Llama 4 Maverick121 tok/s | o3-pro27 tok/s | Llama 4 Maverick has the higher measured throughput. |
| First-answer latencyseconds to first token | Llama 4 Maverick0.95 s | o3-pro84.93 s | Llama 4 Maverick reaches the first token sooner. |
| Context windowmaximum listed tokens | Llama 4 Maverick1M | o3-pro200K | Llama 4 Maverick lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Llama 4 Maverick | o3-pro | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.3% | 32.5% | o3-pro leads |
| AA-GPQA DiamondSource | 67.1% | 84.5% | o3-pro leads |
| AA-HLESource | 4.8% | — | Not comparable |
| AA-Omniscience IndexSource | -41.8% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 87.3% | — | Not comparable |
Math1 benchmarks
| Benchmark | Llama 4 Maverick | o3-pro | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 0.690% | — | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Llama 4 Maverick | o3-pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.0% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Llama 4 Maverick and o3-pro 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 Llama 4 Maverick and o3-pro today?
Llama 4 Maverick: $0.00 input / $0.00 output per 1M tokens o3-pro: $20.00 input / $80.00 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.
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