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Model comparison

Gemini 1.5 Pro vs Llama 4 Scout

Data verified

Head-to-head evidence from 6 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

35.71/100
Margin
4.2pts
winning →
39.87/100
0 category wins0 category wins

Public leaderboard positions: Gemini 1.5 Pro #185 (Supported); Llama 4 Scout #174 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemini 1.5 Pro and Llama 4 Scout share 6 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Gemini 1.5 Pro; 12 to Llama 4 Scout.

Updated July 20, 2026
Shared results
6
Gemini 1.5 Pro only
0
Llama 4 Scout only
12
Comparable categories
0 / 8

Benchmark data for Gemini 1.5 Pro and Llama 4 Scout is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 6 shared benchmark results across 3 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.

Gemini 1.5 Pro is priced at $1.25 input / $5.00 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 2M for Gemini 1.5 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.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGemini 1.5 ProLlama 4 ScoutComparison
Input / output priceUSD per 1M tokensGemini 1.5 Pro$1.25 input / $5 outputLlama 4 Scout$0 input / $0 outputLlama 4 Scout has the lower combined listed price.
Generation speedtokens per secondGemini 1.5 ProNot availableLlama 4 Scout128 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemini 1.5 ProNot availableLlama 4 Scout0.70 sA complete latency comparison is not available.
Context windowmaximum listed tokensGemini 1.5 Pro2MLlama 4 Scout10MLlama 4 Scout lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemini 1.5 ProLlama 4 ScoutResult
AA Agentic IndexSource 1.1%Not comparable
τ²-bench resultsSource 15.5%Not comparable
GDPval-AASource 0.0%Not comparable
GDPval-AASource 90Not comparable
Coding
BenchmarkGemini 1.5 ProLlama 4 ScoutResult
AA Coding IndexSource 23.6%8.2%Gemini 1.5 Pro leads
AA-SciCodeSource 29.5%17.0%Gemini 1.5 Pro leads
Reasoning
BenchmarkGemini 1.5 ProLlama 4 ScoutResult
AA-LCRSource 25.8%Not comparable
CritPtSource 0.0%Not comparable
Knowledge
BenchmarkGemini 1.5 ProLlama 4 ScoutResult
Artificial Analysis Intelligence IndexSource 10.0%10.0%Llama 4 Scout leads
AA-GPQA DiamondSource 58.9%58.7%Gemini 1.5 Pro leads
AA-HLESource 4.9%4.3%Gemini 1.5 Pro leads
AA-Omniscience IndexSource -52.4%Not comparable
AA-Omniscience AccuracySource 14.6%Not comparable
AA-Omniscience Hallucination RateSource 78.3%Not comparable
Math
BenchmarkGemini 1.5 ProLlama 4 ScoutResult
FrontierMath v2 (Tiers 1-3)Source 0.000%Not comparable
Multimodal
BenchmarkGemini 1.5 ProLlama 4 ScoutResult
AA-MMMU-ProSource 55.0%52.9%Gemini 1.5 Pro leads
Design Arena WebsiteSource 783Not comparable
Inst. Following
BenchmarkGemini 1.5 ProLlama 4 ScoutResult
AA-IFBenchSource 39.5%Not comparable
Frequently Asked Questions (3)

Can I compare Gemini 1.5 Pro 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 Gemini 1.5 Pro and Llama 4 Scout today?

Gemini 1.5 Pro: $1.25 input / $5.00 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.

Gemini 1.5 Pro
API / mo$4,688
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Llama 4 Scout
API / mo$0
Self-host / mo$2,278
Break-even
Model the full break-even

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Last updated: July 20, 2026

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