Model comparison
Llama 4 Scout vs Nemotron 3 Super 100B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Llama 4 Scout #174 (Supported); Nemotron 3 Super 100B #117 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Llama 4 Scout and Nemotron 3 Super 100B share 0 comparable benchmark results. 0 of 8 categories are comparable. 18 results are unique to Llama 4 Scout; 1 to Nemotron 3 Super 100B.
Updated July 21, 2026- Shared results
- 0
- Llama 4 Scout only
- 18
- Nemotron 3 Super 100B only
- 1
- Comparable categories
- 0 / 8
Benchmark data for Llama 4 Scout and Nemotron 3 Super 100B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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.
Llama 4 Scout has the larger context window at 10M, compared with 1M for Nemotron 3 Super 100B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Llama 4 Scout | Nemotron 3 Super 100B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Llama 4 Scout$0 input / $0 output | Nemotron 3 Super 100B$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Llama 4 Scout128 tok/s | Nemotron 3 Super 100B367 tok/s | Nemotron 3 Super 100B has the higher measured throughput. |
| First-answer latencyseconds to first token | Llama 4 Scout0.70 s | Nemotron 3 Super 100B0.71 s | Llama 4 Scout reaches the first token sooner. |
| Context windowmaximum listed tokens | Llama 4 Scout10M | Nemotron 3 Super 100B1M | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Llama 4 Scout | Nemotron 3 Super 100B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 10.0% | — | Not comparable |
| AA-GPQA DiamondSource | 58.7% | — | Not comparable |
| AA-HLESource | 4.3% | — | Not comparable |
| AA-Omniscience IndexSource | -52.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 14.6% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 78.3% | — | Not comparable |
Math1 benchmarks
| Benchmark | Llama 4 Scout | Nemotron 3 Super 100B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 0.000% | — | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Llama 4 Scout | Nemotron 3 Super 100B | Result |
|---|---|---|---|
| AA-IFBenchSource | 39.5% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Llama 4 Scout and Nemotron 3 Super 100B 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 Nemotron 3 Super 100B today?
Llama 4 Scout: $0.00 input / $0.00 output per 1M tokens Nemotron 3 Super 100B: $0.00 input / $0.00 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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