Model comparison
Llama 4 Scout vs o3
Head-to-head evidence from 14 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Llama 4 Scout #174 (Supported); o3 #131 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Scout and o3 share 14 comparable benchmark results. 0 of 8 categories are comparable. 4 results are unique to Llama 4 Scout; 2 to o3.
Updated July 20, 2026- Shared results
- 14
- Llama 4 Scout only
- 4
- o3 only
- 2
- Comparable categories
- 0 / 8
Benchmark data for Llama 4 Scout and o3 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 7 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.
o3 is priced at $2.00 input / $8.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Scout. Llama 4 Scout has the larger context window at 10M, compared with 200K for o3.
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 Scout | Δ | o3 |
|---|---|---|---|
| Math | Llama 4 ScoutNot measured | MarginNo overlap | o314.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 0.000%B 18.685%Winner: o3Δ 18.7FrontierMath v2 (Tiers 1-3): Llama 4 Scout scored 0.000%; o3 scored 18.685%. o3 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Llama 4 Scout | o3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Scout$0 input / $0 output | o3$2 input / $8 output | Llama 4 Scout has the lower combined listed price. |
| Generation speedtokens per second | Llama 4 Scout128 tok/s | o3118 tok/s | Llama 4 Scout has the higher measured throughput. |
| First-answer latencyseconds to first token | Llama 4 Scout0.70 s | o35.38 s | Llama 4 Scout reaches the first token sooner. |
| Context windowmaximum listed tokens | Llama 4 Scout10M | o3200K | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Llama 4 Scout | o3 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 10.0% | 30.4% | o3 leads |
| AA-GPQA DiamondSource | 58.7% | 82.7% | o3 leads |
| AA-HLESource | 4.3% | 20.0% | o3 leads |
| AA-Omniscience IndexSource | -52.4% | -15.3% | o3 leads |
| AA-Omniscience AccuracySource | 14.6% | 38.4% | o3 leads |
| AA-Omniscience Hallucination RateSource | 78.3% | 87.1% | Llama 4 Scout leads |
Math3 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Llama 4 Scout | o3 | Result |
|---|---|---|---|
| AA-IFBenchSource | 39.5% | 71.4% | o3 leads |
Frequently Asked Questions (3)
Can I compare Llama 4 Scout and o3 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 Scout and o3 today?
Llama 4 Scout: $0.00 input / $0.00 output per 1M tokens o3: $2.00 input / $8.00 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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