Model comparison
Llama 4 Scout vs o1
Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Llama 4 Scout #183 (Supported); o1 #136 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Scout and o1 share 13 comparable benchmark results. 0 of 8 categories are comparable. 5 results are unique to Llama 4 Scout; 3 to o1.
Updated July 24, 2026- Shared results
- 13
- Llama 4 Scout only
- 5
- o1 only
- 3
- Comparable categories
- 0 / 8
Benchmark data for Llama 4 Scout and o1 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 6 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.
o1 is priced at $15.00 input / $60.00 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 o1.
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 | o1 |
|---|---|---|---|
| Knowledge | Llama 4 ScoutNot measured | MarginNo overlap | o175.7 |
| Math | Llama 4 ScoutNot measured | MarginNo overlap | o19.3 |
| Inst. Following | Llama 4 ScoutNot measured | MarginNo overlap | o192.2 |
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 9.310%Winner: o1Δ 9.3FrontierMath v2 (Tiers 1-3): Llama 4 Scout scored 0.000%; o1 scored 9.310%. o1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Llama 4 Scout | o1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Scout$0 input / $0 output | o1$15 input / $60 output | Llama 4 Scout has the lower combined listed price. |
| Generation speedtokens per second | Llama 4 Scout128 tok/s | o198 tok/s | Llama 4 Scout has the higher measured throughput. |
| First-answer latencyseconds to first token | Llama 4 Scout0.70 s | o132.29 s | Llama 4 Scout reaches the first token sooner. |
| Context windowmaximum listed tokens | Llama 4 Scout10M | o1200K | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Llama 4 Scout | o1 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 10.0% | 23.4% | o1 leads |
| AA-GPQA DiamondSource | 58.7% | 74.7% | o1 leads |
| AA-HLESource | 4.3% | 7.7% | o1 leads |
| AA-Omniscience IndexSource | -52.4% | -10.5% | o1 leads |
| AA-Omniscience AccuracySource | 14.6% | 34.7% | o1 leads |
| AA-Omniscience Hallucination RateSource | 78.3% | 69.3% | o1 leads |
| MMLUSource | — | 91.8% | Not comparable |
| GPQASource | — | 75.7% | Not comparable |
Math1 benchmarks
| Benchmark | Llama 4 Scout | o1 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 0.000% | 9.310% | o1 leads |
Multimodal2 benchmarks
Frequently Asked Questions (3)
Can I compare Llama 4 Scout and o1 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 o1 today?
Llama 4 Scout: $0.00 input / $0.00 output per 1M tokens o1: $15.00 input / $60.00 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.