Model comparison
Celeris-1 vs Llama 4 Scout
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: Celeris-1 unranked (Not scored); Llama 4 Scout #174 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Celeris-1 and Llama 4 Scout share 0 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to Celeris-1; 18 to Llama 4 Scout.
Updated July 24, 2026- Shared results
- 0
- Celeris-1 only
- 1
- Llama 4 Scout only
- 18
- Comparable categories
- 0 / 8
Benchmark data for Celeris-1 and Llama 4 Scout 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.
Celeris-1 is priced at $2.00 input / $6.00 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 8K for Celeris-1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Celeris-1 | Llama 4 Scout | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Celeris-1$2 input / $6 output | Llama 4 Scout$0 input / $0 output | Llama 4 Scout has the lower combined listed price. |
| Generation speedtokens per second | Celeris-1Not available | Llama 4 Scout128 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Celeris-1Not available | Llama 4 Scout0.70 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Celeris-18K | Llama 4 Scout10M | Llama 4 Scout lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | Celeris-1 | Llama 4 Scout | Result |
|---|---|---|---|
| MMLU-ProSource | 75.9% | — | Not comparable |
| 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 | Celeris-1 | Llama 4 Scout | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | — | 0.000% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Celeris-1 | Llama 4 Scout | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 39.5% | Not comparable |
Frequently Asked Questions (3)
Can I compare Celeris-1 and Llama 4 Scout 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 Celeris-1 and Llama 4 Scout today?
Celeris-1: $2.00 input / $6.00 output per 1M tokens Llama 4 Scout: $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.
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.